{"id":888,"date":"2026-10-12T07:35:27","date_gmt":"2026-10-12T07:35:27","guid":{"rendered":"https:\/\/helpwithmygisassignment.com\/blog\/?p=888"},"modified":"2026-10-12T07:35:27","modified_gmt":"2026-10-12T07:35:27","slug":"site-suitability-analysis-gis","status":"publish","type":"post","link":"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/","title":{"rendered":"Site Suitability Analysis using Multi-Criteria Evaluation (MCE) in GIS"},"content":{"rendered":"<div>\n<div><\/div>\n<div>\n<div>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_89 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Site_Suitability_Analysis_using_Multi-Criteria_Evaluation_MCE_in_GIS\" >Site Suitability Analysis using Multi-Criteria Evaluation (MCE) in GIS<\/a><ul class='ez-toc-list-level-2' ><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Introduction_What_Is_Multi-Criteria_Evaluation_in_GIS\" >Introduction: What Is Multi-Criteria Evaluation in GIS?<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#The_MCE_workflow_at_a_glance\" >The MCE workflow at a glance<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Phase_1_Criteria_Selection_and_Constraint_Identification\" >Phase 1: Criteria Selection and Constraint Identification<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_11_Define_the_objective_and_study_area\" >Step 1.1: Define the objective and study area<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_12_Identify_factors\" >Step 1.2: Identify factors<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_13_Identify_constraints\" >Step 1.3: Identify constraints<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Factors_versus_constraints\" >Factors versus constraints<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Phase_2_Data_Preparation_and_Standardization\" >Phase 2: Data Preparation and Standardization<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_21_Collect_and_inspect_the_input_data\" >Step 2.1: Collect and inspect the input data<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_22_Standardize_the_coordinate_system_and_raster_grid\" >Step 2.2: Standardize the coordinate system and raster grid<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_23_Convert_vector_data_to_raster_where_necessary\" >Step 2.3: Convert vector data to raster where necessary<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_24_Create_exclusion_buffers\" >Step 2.4: Create exclusion buffers<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_25_Reclassify_factors_onto_a_common_suitability_scale\" >Step 2.5: Reclassify factors onto a common suitability scale<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Phase_3_Weight_Assignment_and_Overlay_Analysis\" >Phase 3: Weight Assignment and Overlay Analysis<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_31_Choose_a_method_for_assigning_weights\" >Step 3.1: Choose a method for assigning weights<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_32_Assign_example_weights\" >Step 3.2: Assign example weights<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_33_Use_pairwise_comparison_with_AHP\" >Step 3.3: Use pairwise comparison with AHP<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_34_Calculate_the_weighted_suitability_score\" >Step 3.4: Calculate the weighted suitability score<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_35_Run_Weighted_Overlay_in_ArcGIS_Pro\" >Step 3.5: Run Weighted Overlay in ArcGIS Pro<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_36_Calculate_the_weighted_overlay_in_QGIS\" >Step 3.6: Calculate the weighted overlay in QGIS<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-22\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Why_constraints_should_not_simply_receive_a_low_score\" >Why constraints should not simply receive a low score<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-23\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Phase_4_Output_Sensitivity_and_Validation\" >Phase 4: Output Sensitivity and Validation<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-24\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_41_Classify_the_suitability_raster\" >Step 4.1: Classify the suitability raster<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-25\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_42_Perform_sensitivity_analysis\" >Step 4.2: Perform sensitivity analysis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-26\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_43_Validate_the_result\" >Step 4.3: Validate the result<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-27\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Step_44_Extract_and_compare_candidate_sites\" >Step 4.4: Extract and compare candidate sites<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-28\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Conclusion_Key_Takeaways_for_Student_Projects\" >Conclusion: Key Takeaways for Student Projects<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-29\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/#Further_reading\" >Further reading<\/a><\/li><\/ul><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"Site_Suitability_Analysis_using_Multi-Criteria_Evaluation_MCE_in_GIS\"><\/span>Site Suitability Analysis using Multi-Criteria Evaluation (MCE) in GIS<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p>A practical workflow for university GIS projects using QGIS and ArcGIS Pro<\/p>\n<p>Site suitability analysis is one of the most useful applications of GIS because it helps researchers identify locations that best meet a set of environmental, economic, technical, and social requirements.<\/p>\n<p>This guide follows a hypothetical solar farm site-selection project to explain the complete workflow, from choosing criteria to producing and validating a suitability map.<\/p>\n<p>The central idea is simple: prepare geographic data representing different site-selection criteria, standardize those criteria onto a common scale, assign relative importance to each factor, and combine them into a final suitability surface\u2014while excluding locations where development is not permitted.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-941\" src=\"https:\/\/helpwithmygisassignment.com\/blog\/wp-content\/uploads\/2026\/10\/Gemini_Generated_Image_aehd01aehd01aehd-1024x559.jpg\" alt=\"Prompt: A clean, professional technical diagram and GIS interface layout for an academic tutorial. On the left side, a clear flowchart illustrates a Multi-Criteria Evaluation (MCE) workflow: raw data layers (DEM, Land Cover, Roads, Solar Irradiance) flowing into a standardized reclassification step (1\u20139 scale), followed by a weighted overlay box leading to a final suitability raster. On the right side, a simulated QGIS map canvas displays a professional site-suitability layout complete with a clear legend, scale bar, grid lines, and a classified raster showing distinct green &quot;High Suitability&quot; zones and red &quot;Excluded&quot; zones. The style is crisp, precise, and educational, resembling an expert GIS lab report figure or textbook illustration.\" width=\"1024\" height=\"559\" srcset=\"https:\/\/helpwithmygisassignment.com\/blog\/wp-content\/uploads\/2026\/10\/Gemini_Generated_Image_aehd01aehd01aehd-1024x559.jpg 1024w, https:\/\/helpwithmygisassignment.com\/blog\/wp-content\/uploads\/2026\/10\/Gemini_Generated_Image_aehd01aehd01aehd-300x164.jpg 300w, https:\/\/helpwithmygisassignment.com\/blog\/wp-content\/uploads\/2026\/10\/Gemini_Generated_Image_aehd01aehd01aehd-768x419.jpg 768w, https:\/\/helpwithmygisassignment.com\/blog\/wp-content\/uploads\/2026\/10\/Gemini_Generated_Image_aehd01aehd01aehd.jpg 1408w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Introduction_What_Is_Multi-Criteria_Evaluation_in_GIS\"><\/span>Introduction: What Is Multi-Criteria Evaluation in GIS?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Multi-Criteria Evaluation (MCE) is a structured method for evaluating locations against several criteria simultaneously. When combined with GIS, it allows spatial data to be compared and integrated to identify areas that are more or less suitable for a particular purpose.<\/p>\n<p>For example, a proposed solar farm may require:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p>Relatively flat terrain to reduce construction complexity.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>High solar irradiation to support electricity generation.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Reasonable access to roads and electrical infrastructure.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Suitable land cover that avoids sensitive ecosystems.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Separation from legally protected areas and other restricted locations.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>No single dataset can answer all these questions. A solar-resource map may identify areas with excellent sunshine, but some of those locations may be too steep, difficult to access, or environmentally restricted.<\/p>\n<p>MCE combines these different considerations into a <a href=\"https:\/\/helpwithmygisassignment.com\/blog\/ols-vs-gwr-spatial-regression\/\">spatial decision mode<\/a>l.<\/p>\n<div>\n<h3><span class=\"ez-toc-section\" id=\"The_MCE_workflow_at_a_glance\"><\/span>The MCE workflow at a glance<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div>\n<p>1. Select criteria and constraints<\/p>\n<p>Define what improves suitability and what rules a site out.<\/p>\n<\/div>\n<div><\/div>\n<div>\n<p>2. Prepare and standardize spatial data<\/p>\n<p>Create aligned rasters and reclassify factor values to a common scale.<\/p>\n<\/div>\n<div><\/div>\n<div>\n<p>3. Assign weights and overlay factors<\/p>\n<p>Combine standardized factors using a documented decision model.<\/p>\n<\/div>\n<div><\/div>\n<div>\n<p>4. Apply exclusions and classify results<\/p>\n<p>Remove unsuitable locations and identify the most promising areas.<\/p>\n<\/div>\n<div><\/div>\n<div>\n<p>5. Validate and test sensitivity<\/p>\n<p>Check assumptions, alternative weights, and real-world constraints.<\/p>\n<\/div>\n<\/div>\n<p>The process follows a widely used GIS-based multi-criteria decision analysis approach: transform the criteria to a common scale, then weight and combine them. See Esri&#8217;s <a href=\"https:\/\/doc.esri.com\/en\/arcgis-pro\/latest\/tool-reference\/spatial-analyst\/how-multicriteria-overlay-works.html\" target=\"_blank\" rel=\"noopener\">Multicriteria Overlay documentation<\/a>.<\/p>\n<p>The same principles apply to landfill placement, hospital location planning, wind farms, conservation prioritization, and other spatial decision problems. The criteria and exclusion rules must change to suit each application.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Phase_1_Criteria_Selection_and_Constraint_Identification\"><\/span>Phase 1: Criteria Selection and Constraint Identification<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The first stage is deciding which geographic conditions make a location suitable and which conditions automatically disqualify it.<\/p>\n<p>This distinction is fundamental to a reliable MCE model.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_11_Define_the_objective_and_study_area\"><\/span>Step 1.1: Define the objective and study area<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>For this example, assume the objective is:<\/p>\n<p>Identify potentially suitable locations for a utility-scale solar farm within a defined county or planning region.<\/p>\n<p>Before processing data, document the basic requirements:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Define the study area boundary.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Specify the type and approximate size of facility being considered.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Establish the required map resolution and geographic scale.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Identify environmental, engineering, planning, and legal requirements.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Decide what constitutes a high-suitability result.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>A rooftop solar installation and a utility-scale solar farm have different spatial requirements. A useful model must reflect the type of facility being evaluated.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_12_Identify_factors\"><\/span>Step 1.2: Identify factors<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>A factor is a condition that affects how suitable a location is. Its influence can vary across the study area rather than simply classifying every location as acceptable or unacceptable.<\/p>\n<p>For a solar farm, possible factors include slope, solar irradiation, distance to roads, and land cover.<\/p>\n<div>\n<table>\n<tbody>\n<tr>\n<th>Factor<\/th>\n<th>Example dataset<\/th>\n<th>Suitability relationship<\/th>\n<\/tr>\n<tr>\n<td>Slope<\/td>\n<td>Digital Elevation Model (DEM)<\/td>\n<td>Flatter terrain is generally more suitable<\/td>\n<\/tr>\n<tr>\n<td>Solar irradiation<\/td>\n<td>Solar radiation or irradiance raster<\/td>\n<td>Greater usable solar resource is generally more suitable<\/td>\n<\/tr>\n<tr>\n<td>Distance to roads<\/td>\n<td>Road network<\/td>\n<td>Accessible locations may be more suitable<\/td>\n<\/tr>\n<tr>\n<td>Land cover<\/td>\n<td>Land-use or land-cover classification<\/td>\n<td>Previously disturbed or appropriate open land may be preferred<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>The relationships above are examples, not universal engineering rules. Some facilities require a minimum road setback, for example, even though access to roads is desirable. That setback should be treated as a separate constraint when appropriate.<\/p>\n<p>Practical advice: Avoid including several highly correlated factors without justification. For instance, road distance and distance to electricity infrastructure may partly represent the same accessibility advantage. Giving both excessive weight can unintentionally count the same consideration twice.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_13_Identify_constraints\"><\/span>Step 1.3: Identify constraints<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>A constraint is a condition that excludes a location from consideration, regardless of how well it scores on other factors.<\/p>\n<p>Possible solar-farm constraints include:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p>Protected areas where the proposed development is prohibited.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Water bodies and wetlands, including applicable protection buffers.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Legally restricted zones.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Existing built-up areas where construction is not permitted.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Areas exceeding a clearly justified engineering limit.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Land subject to other binding planning restrictions.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>For example, a protected wetland should not become an acceptable candidate simply because it has excellent solar irradiation and convenient road access.<\/p>\n<p>This is why constraints should be separated from suitability factors.<\/p>\n<div>\n<h3><span class=\"ez-toc-section\" id=\"Factors_versus_constraints\"><\/span>Factors versus constraints<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div>\n<div>\n<p>Factor<\/p>\n<p>Ranks locations from relatively unsuitable to highly suitable.<\/p>\n<p>Example: slope score of 1\u20139<\/p>\n<\/div>\n<div>\n<p>Constraint<\/p>\n<p>Marks locations as eligible or excluded under a defined rule.<\/p>\n<p>Example: prohibited protected land<\/p>\n<\/div>\n<\/div>\n<\/div>\n<p>In raster analysis, constraints are often represented by a Boolean mask: one value identifies eligible cells, and another identifies excluded cells. Alternatively, excluded areas can be assigned NoData or an explicit restricted value supported by the analysis tool.<\/p>\n<p>Important: Use applicable legislation, official protected-area boundaries, planning requirements, and documented technical standards to set exclusions. A student suitability model is a preliminary screening tool, not a substitute for environmental assessment, land-rights checks, engineering surveys, or regulatory approval.<\/p>\n<div><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Phase_2_Data_Preparation_and_Standardization\"><\/span>Phase 2: Data Preparation and Standardization<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Once the criteria are defined, prepare the input datasets so that they can be combined correctly.<\/p>\n<p>The central task is to convert the different inputs into spatially aligned raster layers with comparable suitability scores.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_21_Collect_and_inspect_the_input_data\"><\/span>Step 2.1: Collect and inspect the input data<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>For a solar-farm exercise, gather:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>A study-area boundary polygon.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>A DEM for calculating slope.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>A solar-resource raster.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>A road-network dataset.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>A land-cover dataset.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Protected-area and other exclusion-zone boundaries.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>Inspect the source, date, scale or resolution, CRS, data quality, and intended use of each dataset.<\/p>\n<p>Possible sources include government mapping agencies, official land-cover products, trusted elevation datasets, and documented solar-resource datasets.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_22_Standardize_the_coordinate_system_and_raster_grid\"><\/span>Step 2.2: Standardize the coordinate system and raster grid<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Raster overlay requires careful alignment. Two rasters can appear to overlap on the map while their pixel grids are offset from each other.<\/p>\n<p>Before combining rasters:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Reproject the input data into a suitable projected CRS for the study area.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Choose a common cell size appropriate to the data and decision scale.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Set a common processing extent.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Align pixel origins and grids using a reference or snap raster.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Check NoData handling and ensure that all output rasters cover the intended study area.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>The chosen cell size should reflect the coarsest meaningful source data and the intended decision scale. Resampling a 100 m source to 10 m does not create genuine 10 m detail.<\/p>\n<p>For more on raster alignment, see the <a href=\"https:\/\/docs.qgis.org\/4.2\/en\/docs\/user_manual\/processing_algs\/qgis\/rastertools.html\" target=\"_blank\" rel=\"noopener\">QGIS raster tools documentation<\/a>.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_23_Convert_vector_data_to_raster_where_necessary\"><\/span>Step 2.3: Convert vector data to raster where necessary<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Weighted raster overlay requires criteria to be represented on a compatible raster grid. Not all inputs begin in raster format, so you may need to derive or convert some datasets.<\/p>\n<p>Slope from a DEM<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p>In QGIS, open the Processing Toolbox and locate the Slope algorithm under terrain analysis.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>In ArcGIS Pro, use Slope in the Spatial Analyst or relevant raster-analysis tools.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Save the result in a suitable raster format and inspect its units, such as degrees or percent rise.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>Land cover from polygons<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p>In QGIS, use Rasterize (vector to raster) through the Processing Toolbox.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>In ArcGIS Pro, use Polygon To Raster.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Use an appropriate categorical field to encode land-cover classes.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Ensure the raster cell size, extent, and alignment match the other analysis rasters.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>Do not treat categorical class codes such as 1, 2, and 3 as suitability scores automatically. Those numbers may simply be identifiers for forest, grassland, and urban land. Reclassify them according to your documented criteria.<\/p>\n<p>Distance to roads<\/p>\n<p>A road network is usually converted into a distance raster rather than simply rasterizing road locations.<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p>In QGIS, use a suitable proximity or distance algorithm.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>In ArcGIS Pro, use Distance Accumulation or an appropriate Euclidean-distance tool.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Confirm the units and whether the distance is straight-line or network-based.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>For local site screening, straight-line distance may be adequate for an initial model. Road-network travel distance may be more appropriate when accessibility depends on the actual transport network.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_24_Create_exclusion_buffers\"><\/span>Step 2.4: Create exclusion buffers<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Some constraints are based on proximity rather than just the location of a feature itself.<\/p>\n<p>For example, the planning framework may require a buffer around particular water bodies or sensitive facilities.<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Identify the features requiring protection or separation.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Confirm the relevant buffer distance from official requirements or a documented study assumption.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Use the Buffer tool on the relevant vector layers.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Combine the resulting exclusion areas with other constraints.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Convert or rasterize the exclusion zones to align with the analysis grid if your workflow uses raster overlay.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>Do not use arbitrary buffer distances simply because they produce a visually neat map. Every buffer should have a defensible source or be explicitly identified as a modelling assumption.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_25_Reclassify_factors_onto_a_common_suitability_scale\"><\/span>Step 2.5: Reclassify factors onto a common suitability scale<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The input datasets contain different measurements:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p>Slope may be measured in degrees.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Distance to roads may be measured in metres.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Solar irradiation may be measured in energy per unit area over a defined period.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Land cover may contain categorical codes.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>You cannot meaningfully add these raw values together without standardizing what they represent.<\/p>\n<p>Reclassification converts original values into a common scale, such as 1\u20139, where:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p>1 represents very low suitability.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>9 represents very high suitability.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>The direction must be set separately for each factor. For slope, a smaller number of degrees may receive a higher suitability score. For solar irradiation, higher values may receive a higher score. Distance criteria may favour locations closer to roads, subject to any required exclusion buffer.<\/p>\n<p>Here is an illustrative reclassification table for a hypothetical solar-farm model.<\/p>\n<div>\n<table>\n<tbody>\n<tr>\n<th>Factor<\/th>\n<th>Original value<\/th>\n<th>Example suitability score<\/th>\n<\/tr>\n<tr>\n<td>Slope<\/td>\n<td>0\u20133\u00b0<\/td>\n<td>9<\/td>\n<\/tr>\n<tr>\n<td>Slope<\/td>\n<td>Greater than 3\u20135\u00b0<\/td>\n<td>8<\/td>\n<\/tr>\n<tr>\n<td>Slope<\/td>\n<td>Greater than 5\u201310\u00b0<\/td>\n<td>6<\/td>\n<\/tr>\n<tr>\n<td>Slope<\/td>\n<td>Greater than 10\u201315\u00b0<\/td>\n<td>3<\/td>\n<\/tr>\n<tr>\n<td>Slope<\/td>\n<td>Greater than 15\u00b0<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td>Road distance<\/td>\n<td>0\u2013500 m<\/td>\n<td>9<\/td>\n<\/tr>\n<tr>\n<td>Road distance<\/td>\n<td>Greater than 500\u20131,500 m<\/td>\n<td>8<\/td>\n<\/tr>\n<tr>\n<td>Road distance<\/td>\n<td>Greater than 1,500\u20133,000 m<\/td>\n<td>6<\/td>\n<\/tr>\n<tr>\n<td>Road distance<\/td>\n<td>Greater than 3,000\u20135,000 m<\/td>\n<td>3<\/td>\n<\/tr>\n<tr>\n<td>Road distance<\/td>\n<td>Greater than 5,000 m<\/td>\n<td>1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>These thresholds are illustrative only. Actual limits must be determined from technical requirements, site conditions, and the project&#8217;s purpose. The best road-distance range may not be the closest range if access buffers, safety, or other requirements apply.<\/p>\n<p>Use similarly documented scoring tables for solar irradiation and land cover. For categorical land cover, explicitly state which categories are preferred, less preferred, or excluded.<\/p>\n<p>In QGIS:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Open the Processing Toolbox.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Search for Reclassify by Table.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Select the raster band to reclassify.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Enter the minimum and maximum ranges and their new suitability scores.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Assign NoData to categories that should be excluded from the factor raster, where appropriate.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Save each reclassified raster.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>See the <a href=\"https:\/\/docs.qgis.org\/4.2\/en\/docs\/user_manual\/processing_algs\/qgis\/rasteranalysis.html\" target=\"_blank\" rel=\"noopener\">QGIS Reclassify by Table documentation<\/a>.<\/p>\n<p>In ArcGIS Pro:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Open Analysis \u2192 Tools.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Search for Reclassify.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Choose the input raster and the field or values to reclassify.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Specify the new suitability values.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Save the output raster.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>At the end of this stage, every factor should have a clearly documented meaning, a common evaluation scale, and the same aligned raster grid.<\/p>\n<div><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Phase_3_Weight_Assignment_and_Overlay_Analysis\"><\/span>Phase 3: Weight Assignment and Overlay Analysis<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Now that the factor rasters use a common scale, the next question is how much importance each factor should contribute to the final result.<\/p>\n<p>A slope requirement may be more important for one development than road accessibility. A conservation model may prioritize habitat integrity above access to roads. The weights encode these priorities.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_31_Choose_a_method_for_assigning_weights\"><\/span>Step 3.1: Choose a method for assigning weights<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>There are several ways to assign criteria weights.<\/p>\n<p>Equal weighting: Give every factor the same weight. This is simple and useful as a baseline, but it assumes all criteria matter equally.<\/p>\n<p>Expert judgment: Assign weights based on technical knowledge, stakeholder priorities, published standards, or a documented planning framework.<\/p>\n<p>Analytic Hierarchy Process (AHP): Use pairwise comparisons to judge the relative importance of each criterion and derive weights systematically.<\/p>\n<p>AHP is commonly applied to GIS suitability analysis because it provides a structured way to convert expert preferences into numerical weights. It also includes a consistency check to help identify contradictory comparisons. See this <a href=\"https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC10643545\/\" target=\"_blank\" rel=\"noopener\">GIS\u2013AHP site-suitability study<\/a>.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_32_Assign_example_weights\"><\/span>Step 3.2: Assign example weights<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>For this hypothetical solar-farm project, suppose the criteria are weighted as follows:<\/p>\n<div>\n<table>\n<tbody>\n<tr>\n<th>Factor<\/th>\n<th>Example weight<\/th>\n<th>Why it might matter<\/th>\n<\/tr>\n<tr>\n<td>Solar irradiation<\/td>\n<td>35%<\/td>\n<td>Influences the energy resource<\/td>\n<\/tr>\n<tr>\n<td>Slope<\/td>\n<td>25%<\/td>\n<td>Affects terrain suitability and construction<\/td>\n<\/tr>\n<tr>\n<td>Distance to roads<\/td>\n<td>20%<\/td>\n<td>Represents access to transport<\/td>\n<\/tr>\n<tr>\n<td>Land cover<\/td>\n<td>20%<\/td>\n<td>Represents land-use compatibility<\/td>\n<\/tr>\n<tr>\n<td>Total<\/td>\n<td>100%<\/td>\n<td><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>These weights are demonstration values, not recommended weights for every solar-farm project. You should justify your own values using technical evidence, stakeholder requirements, or a documented decision process.<\/p>\n<p>The weights must sum to 100% for the classic ArcGIS Pro Weighted Overlay tool. For formulas using decimal weights, the equivalent total is 1.0.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_33_Use_pairwise_comparison_with_AHP\"><\/span>Step 3.3: Use pairwise comparison with AHP<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>In AHP, you compare the criteria in pairs. For example:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p>How much more important is solar irradiation than slope?<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>How much more important is slope than road access?<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>How important is land-cover compatibility relative to solar irradiation?<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>A common AHP judgment scale ranges from 1 to 9:<\/p>\n<div>\n<table>\n<tbody>\n<tr>\n<th>Value<\/th>\n<th>General meaning<\/th>\n<\/tr>\n<tr>\n<td>1<\/td>\n<td>Equal importance<\/td>\n<\/tr>\n<tr>\n<td>3<\/td>\n<td>Moderate preference<\/td>\n<\/tr>\n<tr>\n<td>5<\/td>\n<td>Strong preference<\/td>\n<\/tr>\n<tr>\n<td>7<\/td>\n<td>Very strong preference<\/td>\n<\/tr>\n<tr>\n<td>9<\/td>\n<td>Extreme preference<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Intermediate values can express judgments between these levels. The reverse comparison uses the reciprocal value.<\/p>\n<p>Once the pairwise matrix is complete, calculate the priority weights and assess consistency. A commonly used guideline is a Consistency Ratio (CR) below about 0.10, although interpretation depends on the method and context. If the ratio exceeds that level, review the judgments for contradictions rather than accepting the weights automatically.<\/p>\n<p>For a student project, you can use a documented AHP calculator or spreadsheet and include the comparison matrix, final weights, and consistency result in an appendix.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_34_Calculate_the_weighted_suitability_score\"><\/span>Step 3.4: Calculate the weighted suitability score<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The weighted linear combination method calculates a score for every eligible raster cell by multiplying each standardized factor by its weight and adding the results.<\/p>\n<p>Conceptually:<\/p>\n<div><span data-math-source=\"S = \\sum_{i=1}^{n} w_i x_i\" data-math-display=\"true\">\\[ S = \\sum_{i=1}^{n} w_i x_i \\]<\/span><\/div>\n<p>Where:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<p><span data-math-source=\"S\" data-math-display=\"false\">\\(S\\)<\/span> is the final suitability score.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p><span data-math-source=\"w_i\" data-math-display=\"false\">\\(w_i\\)<\/span> is the weight of criterion <span data-math-source=\"i\" data-math-display=\"false\">\\(i\\)<\/span>.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p><span data-math-source=\"x_i\" data-math-display=\"false\">\\(x_i\\)<\/span> is the standardized suitability score for that criterion.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p><span data-math-source=\"n\" data-math-display=\"false\">\\(n\\)<\/span> is the number of criteria.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>For the four-factor example:<\/p>\n<div><span data-math-source=\"S = 0.35R + 0.25T + 0.20A + 0.20L\" data-math-display=\"true\">\\[ S = 0.35R + 0.25T + 0.20A + 0.20L \\]<\/span><\/div>\n<p>Here, <span data-math-source=\"R\" data-math-display=\"false\">\\(R\\)<\/span> is the solar-resource score, <span data-math-source=\"T\" data-math-display=\"false\">\\(T\\)<\/span> is the terrain score, <span data-math-source=\"A\" data-math-display=\"false\">\\(A\\)<\/span> is the road-access score, and <span data-math-source=\"L\" data-math-display=\"false\">\\(L\\)<\/span> is the land-cover score.<\/p>\n<p>Suppose a cell has these values:<\/p>\n<div>\n<table>\n<tbody>\n<tr>\n<th>Factor<\/th>\n<th>Score<\/th>\n<th>Weight<\/th>\n<th>Weighted contribution<\/th>\n<\/tr>\n<tr>\n<td>Solar irradiation<\/td>\n<td>8<\/td>\n<td>0.35<\/td>\n<td>2.80<\/td>\n<\/tr>\n<tr>\n<td>Slope<\/td>\n<td>9<\/td>\n<td>0.25<\/td>\n<td>2.25<\/td>\n<\/tr>\n<tr>\n<td>Road accessibility<\/td>\n<td>7<\/td>\n<td>0.20<\/td>\n<td>1.40<\/td>\n<\/tr>\n<tr>\n<td>Land cover<\/td>\n<td>6<\/td>\n<td>0.20<\/td>\n<td>1.20<\/td>\n<\/tr>\n<tr>\n<td>Total suitability<\/td>\n<td><\/td>\n<td><\/td>\n<td>7.65<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Because all four factor scores use the same 1\u20139 scale and the weights sum to 1.0, the combined score remains on that general scale. A score of 7.65 indicates relatively favourable conditions under these particular assumptions, not a universal probability of success.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_35_Run_Weighted_Overlay_in_ArcGIS_Pro\"><\/span>Step 3.5: Run Weighted Overlay in ArcGIS Pro<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>ArcGIS Pro&#8217;s classic Weighted Overlay tool combines integer rasters that have been reclassified to a common suitability scale. Each raster receives a percentage influence, and the percentages must sum to 100. The tool also supports a restricted value for excluding locations. See the <a href=\"https:\/\/doc.esri.com\/en\/arcgis-pro\/latest\/tool-reference\/spatial-analyst\/weighted-overlay.html\" target=\"_blank\" rel=\"noopener\">Weighted Overlay tool documentation<\/a>.<\/p>\n<p>Use the following procedure:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Ensure that the factor rasters are integer rasters and use a compatible evaluation scale.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Open Analysis \u2192 Tools.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Search for Weighted Overlay.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Select the evaluation scale supported by your chosen workflow.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Add the reclassified factor rasters.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Enter their percentage influences.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Check that the percentages total 100.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Configure remap values and restricted values as required.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Set the processing extent, cell size, and alignment environments.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Choose an output raster and run the tool.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>The classic Weighted Overlay tool requires the relevant Spatial Analyst capability. If your workflow needs floating-point output or decimal weights without integer rounding, consider an appropriate weighted-sum or raster-calculator approach instead.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_36_Calculate_the_weighted_overlay_in_QGIS\"><\/span>Step 3.6: Calculate the weighted overlay in QGIS<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>QGIS provides reclassification and raster-calculator workflows for combining suitability rasters. For example, if the standardized raster layers are named <code>solar_suit<\/code>, <code>slope_suit<\/code>, <code>road_suit<\/code>, and <code>landcover_suit<\/code>, the weighted expression is:<\/p>\n<div>\n<div>\n<pre dir=\"ltr\"><code>0.35 * \"solar_suit@1\" +\r\n0.25 * \"slope_suit@1\" +\r\n0.20 * \"road_suit@1\" +\r\n0.20 * \"landcover_suit@1\"<\/code><\/pre>\n<\/div>\n<\/div>\n<p>To run it:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Open Raster \u2192 Raster Calculator or search for Raster Calculator in the Processing Toolbox.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Insert each raster layer using the layer and band names displayed by QGIS.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Enter the weighted expression.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Set the output extent and cell size consistently with the input rasters.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Save the output to a file rather than relying only on a temporary layer.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Inspect the resulting statistics and suitability pattern.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>The expression assumes all input rasters have already been reclassified to a common scale and aligned correctly.<\/p>\n<p>Apply the constraint mask separately so restricted cells are excluded from the candidate areas. In QGIS, you can use a raster mask or an appropriate raster-calculator condition to preserve only eligible cells; do not let excluded cells silently contribute as if they were ordinary low-suitability values.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Why_constraints_should_not_simply_receive_a_low_score\"><\/span>Why constraints should not simply receive a low score<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Weighted overlay is an additive model. A location with a poor score on one factor can still receive a high overall score if the other factors are favourable.<\/p>\n<p>That compensation is acceptable for some preferences, but it is inappropriate for a legal exclusion. A protected area must remain excluded even if all the other criteria score highly.<\/p>\n<p>Therefore, apply the exclusions as a separate mask or supported restricted-value rule and verify that they remain excluded in the final output.<\/p>\n<div><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Phase_4_Output_Sensitivity_and_Validation\"><\/span>Phase 4: Output Sensitivity and Validation<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A suitability map is the result of a model, not an unquestionable statement about the real world. The output depends on the selected data, classifications, weights, and exclusions.<\/p>\n<p>This final phase tests whether the candidate areas remain reasonably consistent when assumptions change and checks whether the results are plausible.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_41_Classify_the_suitability_raster\"><\/span>Step 4.1: Classify the suitability raster<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>After producing the weighted score raster, classify the result into meaningful categories.<\/p>\n<p>For example:<\/p>\n<div>\n<table>\n<tbody>\n<tr>\n<th>Suitability score<\/th>\n<th>Example class<\/th>\n<\/tr>\n<tr>\n<td>1\u20132<\/td>\n<td>Very low suitability<\/td>\n<\/tr>\n<tr>\n<td>3\u20134<\/td>\n<td>Low suitability<\/td>\n<\/tr>\n<tr>\n<td>5\u20136<\/td>\n<td>Moderate suitability<\/td>\n<\/tr>\n<tr>\n<td>7\u20138<\/td>\n<td>High suitability<\/td>\n<\/tr>\n<tr>\n<td>9<\/td>\n<td>Very high suitability<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>These classes are illustrative and should be adapted to the output&#8217;s actual score distribution and the purpose of the project. If a weighted-sum calculation produces fractional values, choose break points that suit the resulting range.<\/p>\n<p>In QGIS, style the output with Singleband pseudocolor or another appropriate raster renderer. In ArcGIS Pro, use Classify or Classified raster symbology, as appropriate to the output.<\/p>\n<p>Use a restrained colour ramp that makes high and low suitability easy to distinguish. Make sure the excluded areas remain visibly distinct from areas that are merely low-scoring.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_42_Perform_sensitivity_analysis\"><\/span>Step 4.2: Perform sensitivity analysis<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Sensitivity analysis tests how much the model&#8217;s results change when its assumptions are adjusted.<\/p>\n<p>For example, your initial model might assign a 20% weight to road access. You could run additional scenarios that assign it 10% and 30%, adjusting the other weights so that the total remains 100%.<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Run the original model with the documented weights.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Create one or more alternative, plausible weighting scenarios.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>If justified, test alternative reclassification thresholds or distance cutoffs.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Compare the high-suitability zones between scenarios.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Record whether the same candidate areas remain prominent or the results change substantially.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>If a candidate location remains highly suitable across several reasonable scenarios, that may suggest that the result is relatively robust to the tested assumptions. If it disappears whenever a single weight changes slightly, the conclusion is more sensitive and should be reported accordingly.<\/p>\n<p>Do not choose the scenario simply because it produces the most attractive or extensive suitable area.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_43_Validate_the_result\"><\/span>Step 4.3: Validate the result<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Validation checks whether the resulting map is reasonable given independent evidence and actual site conditions.<\/p>\n<p>For a solar-farm project:<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Compare candidate areas with known environmental restrictions and official land-use information.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Check that protected zones and required exclusion buffers are absent from the selected sites.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Review terrain and access conditions against source data or reliable reference maps.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Consult relevant planning, environmental, and engineering information.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Where possible, conduct field verification or a more detailed site investigation.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Document uncertain inputs and limitations.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>A site may score highly in the raster model but still be unsuitable because of land ownership, grid-connection cost, local planning rules, biodiversity impacts, or geotechnical conditions that were not represented.<\/p>\n<p>For a thesis: Record the input datasets, resolution, CRS, reclassification tables, weights, constraint criteria, overlay formula, validation methods, and sensitivity results. This makes the model reproducible and allows another researcher to understand why the candidate areas were selected.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Step_44_Extract_and_compare_candidate_sites\"><\/span>Step 4.4: Extract and compare candidate sites<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The suitability raster identifies locations, but a real development usually needs contiguous areas large enough for the proposed facility.<\/p>\n<ul>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Select the high-suitability class or a defensible score threshold.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Convert eligible high-scoring raster cells to polygons if needed.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Dissolve or group adjacent cells into candidate zones.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Remove patches that are too small for the intended facility, using a justified minimum-area requirement.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Inspect the candidate polygons on the map alongside constraints and reference layers.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<div><input disabled=\"disabled\" type=\"checkbox\" \/><label>Rank the remaining candidates using additional project requirements where appropriate.<\/label><\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<p>The final output should present the strongest candidate areas, but it should also show enough information for a reviewer to understand how they were identified.<\/p>\n<div><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion_Key_Takeaways_for_Student_Projects\"><\/span>Conclusion: Key Takeaways for Student Projects<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Site suitability analysis using Multi-Criteria Evaluation combines different spatial datasets into a consistent, documented decision model.<\/p>\n<p>The essential stages are:<\/p>\n<ol>\n<li>\n<div>\n<div>\n<p>Select criteria and constraints that reflect the actual decision problem.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Prepare the data with a suitable CRS, consistent raster grids, appropriate distances and buffers, and documented reclassification scores.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Assign weights and combine factors using a justified method such as expert weighting or AHP.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Apply hard exclusions so legally or environmentally restricted locations cannot become suitable through a high weighted score.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p>Test sensitivity and validate the results before interpreting the map or recommending candidate sites.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ol>\n<p>The most important lesson is that a suitability model is only as defensible as its assumptions. Clear criteria, justified weights, consistent data preparation, and careful validation matter more than producing a colourful final raster.<\/p>\n<p>For a university assignment, aim to show not just where the model identifies suitable areas, but also why those areas score highly, which assumptions influence the outcome, and what further checks would be required before a real-world decision.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Further_reading\"><\/span>Further reading<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>\n<div>\n<div>\n<p><a href=\"https:\/\/doc.esri.com\/en\/arcgis-pro\/latest\/tool-reference\/spatial-analyst\/how-weighted-overlay-works.html\" target=\"_blank\" rel=\"noopener\">Esri: How Weighted Overlay Works<\/a> \u2014 common evaluation scales, weights, and raster combination.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p><a href=\"https:\/\/doc.esri.com\/en\/arcgis-pro\/latest\/tool-reference\/spatial-analyst\/multicriteria-overlay.html\" target=\"_blank\" rel=\"noopener\">Esri: Multicriteria Overlay<\/a> \u2014 alternative overlay methods and criteria standardization.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p><a href=\"https:\/\/docs.qgis.org\/4.2\/en\/docs\/user_manual\/processing_algs\/qgis\/rasteranalysis.html\" target=\"_blank\" rel=\"noopener\">QGIS: Reclassify by Table<\/a> \u2014 converting raster ranges to standardized class values.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p><a href=\"https:\/\/docs.qgis.org\/4.2\/en\/docs\/user_manual\/processing_algs\/qgis\/rastertools.html\" target=\"_blank\" rel=\"noopener\">QGIS: Raster Tools<\/a> \u2014 raster alignment and grid preparation.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<li>\n<div>\n<div>\n<p><a href=\"https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC10643545\/\" target=\"_blank\" rel=\"noopener\">GIS\u2013AHP Site Suitability Study<\/a> \u2014 an example of pairwise comparisons and consistency assessment in spatial suitability modelling.<\/p>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Site Suitability Analysis using Multi-Criteria Evaluation (MCE) in GIS A practical workflow for university GIS projects using QGIS and ArcGIS Pro Site suitability analysis is one of the most useful applications of GIS because it helps researchers identify locations that best meet a set of environmental, economic, technical, and social requirements. This guide follows a &#8230; <a title=\"Site Suitability Analysis using Multi-Criteria Evaluation (MCE) in GIS\" class=\"read-more\" href=\"https:\/\/helpwithmygisassignment.com\/blog\/site-suitability-analysis-gis\/\" aria-label=\"Read more about Site Suitability Analysis using Multi-Criteria Evaluation (MCE) in GIS\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":941,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-888","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-gis-articles"],"_links":{"self":[{"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/posts\/888","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/comments?post=888"}],"version-history":[{"count":4,"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/posts\/888\/revisions"}],"predecessor-version":[{"id":942,"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/posts\/888\/revisions\/942"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/media\/941"}],"wp:attachment":[{"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/media?parent=888"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/categories?post=888"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/helpwithmygisassignment.com\/blog\/wp-json\/wp\/v2\/tags?post=888"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}