{ "culture": "en-ZA", "name": "", "guid": "", "catalogPath": "", "snippet": "Vector dataset representing relative vulnerability levels for district municipalities in KwaZulu\u2011Natal (KZN). District\u2011level vulnerability values were derived by spatially aggregating local\u2011municipality vulnerability indicators using centroid\u2011based spatial joins and summation. The dataset supports district\u2011scale disaster risk assessment, comparison, and strategic planning.", "description": "
This dataset represents a district\u2011level vulnerability assessment for KwaZulu\u2011Natal, produced by aggregating local\u2011municipality vulnerability indicators to district municipality boundaries. The vulnerability modelling reflects relative vulnerability levels associated with social, economic, structural, and environmental dimensions and is intended to support disaster risk assessment and planning at district scale.<\/p>
Local\u2011municipality vulnerability indicators were first calculated at municipal level using demographic, socio\u2011economic, service delivery, and land\u2011use indicators. Social vulnerability indicators included the proportion of vulnerable age groups (population younger than 14 years and older than 65 years), food insecurity indicators (child and adult hunger), and poverty\u2011related variables. These indicators were combined into composite municipal vulnerability indices.<\/p>
For district\u2011level aggregation, centroid point features were generated from local municipality polygons<\/strong>, with each centroid retaining the associated municipal vulnerability attributes. These centroid points were then spatially joined to pre\u2011existing district municipality polygons<\/strong> using a spatial containment relationship.<\/p> A one\u2011to\u2011one spatial join was applied, and municipal\u2011level vulnerability values were summed<\/strong> for each district. The resulting field, Economic and structural vulnerability components incorporated land\u2011use indicators derived from the 2022 national land cover dataset (mining, industrial, and commercial land uses) and infrastructure service indicators, including sanitation type, cooking fuel type, and refuse disposal methods. These indicators collectively capture patterns of economic activity, service provision, and infrastructural resilience.<\/p> Vulnerability values are relative and comparative<\/strong>, not absolute measures of risk. This dataset represents a screening\u2011level analytical product and does not provide real\u2011time or predictive vulnerability information.<\/p><\/div><\/div><\/div><\/div>",
"summary": "Vector dataset representing relative vulnerability levels for district municipalities in KwaZulu\u2011Natal (KZN). District\u2011level vulnerability values were derived by spatially aggregating local\u2011municipality vulnerability indicators using centroid\u2011based spatial joins and summation. The dataset supports district\u2011scale disaster risk assessment, comparison, and strategic planning.",
"title": "LDR.SRK_DMVulnerability",
"tags": [
"Vulnerability",
"district municipality",
"KwaZulu Natal",
"KZN",
"disaster management",
"social vulnerability",
"economic vulnerability",
"service delivery",
"GIS",
"spatial aggregation"
],
"type": "",
"typeKeywords": [],
"thumbnail": "",
"url": "",
"minScale": 150000000,
"maxScale": 5000,
"spatialReference": "",
"accessInformation": "Municipal Demarcation Board (MDB), Produced by Herman Booysen, SRK Consulting.\nProject context: Disaster Management and climate risk assessment for KwaZulu\u2011Natal.",
"licenseInfo": " This dataset represents a screening\u2011level district vulnerability assessment<\/strong> intended to support strategic disaster risk profiling, planning, and prioritisation.<\/p> It is not suitable<\/strong> for:<\/p> Results should be interpreted comparatively and used alongside supporting datasets, expert judgement, and local contextual knowledge.<\/p><\/div><\/div><\/div><\/div>",
"portalUrl": ""
}TotalVulnerability2<\/strong><\/code>, represents the aggregated vulnerability score for each district municipality, reflecting the combined contribution of local municipalities within the district.<\/p>