Georeferenced Plot-Level Data on Urban Grassland Vegetation in Jelgava, Latvia

Urban grasslands are widespread elements of cities, yet plot-level records combining taxon-specific cover with explicit geographic coordinates remain unevenly available across the Baltic region. This Data Descriptor presents vegetation data collected across Jelgava, Latvia, on 12 survey dates from 4 June to 25 August 2025. A two-resolution spatial grid, comprising 500 × 500 m cells in central Jelgava and 1 × 1 km cells in peripheral areas, defined 104 candidate sampling locations. One 1 × 1 m quadrat was planned per location; vegetation surveys were completed at 102 plots, while two locations (Plot IDs 57 and 66) remained unsurveyed. For each completed plot, vascular plant taxa were recorded, and their projective cover was visually estimated as a percentage. The dataset integrates plot identifiers, location descriptions, geographic coordinates, survey dates, taxonomic information, and taxon-level cover values. It contains 131 taxon rows, of which 129 have at least one recorded occurrence, and 1042 positive taxon-by-plot observations. Taxon richness ranges from 5 to 19 taxa per completed plot, with a median of 10. Data validation included checks of survey status, plot-identifier uniqueness, geographic coordinates, and taxon-cover values. The dataset provides a location-referenced baseline for urban vegetation inventories, descriptive spatial and comparative analyses, teaching, and future location-based comparisons. For reuse, Plot IDs 57 and 66 should be treated as unsurveyed observations rather than as zero-cover vegetation records, and the spatial, seasonal, and taxonomic limitations of the dataset should be considered.

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Published
2026-11-04
DOI
https://doi.org/10.3390/data11110295
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Botany and Plant Ecology Studies
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article

Georeferenced Plot-Level Data on Urban Grassland Vegetation in Jelgava, Latvia

Inga Grīnfelde, Jovita Pilecka-Uļčugačeva, Inga Straupe, Līga Liepa
Data
Botany and Plant Ecology Studies
article

Georeferenced Plot-Level Data on Urban Grassland Vegetation in Jelgava, Latvia

Inga Grīnfelde, Jovita Pilecka-Uļčugačeva, Inga Straupe, Līga Liepa
article en

Abstract

Urban grasslands are widespread elements of cities, yet plot-level records combining taxon-specific cover with explicit geographic coordinates remain unevenly available across the Baltic region. This Data Descriptor presents vegetation data collected across Jelgava, Latvia, on 12 survey dates from 4 June to 25 August 2025. A two-resolution spatial grid, comprising 500 × 500 m cells in central Jelgava and 1 × 1 km cells in peripheral areas, defined 104 candidate sampling locations. One 1 × 1 m quadrat was planned per location; vegetation surveys were completed at 102 plots, while two locations (Plot IDs 57 and 66) remained unsurveyed. For each completed plot, vascular plant taxa were recorded, and their projective cover was visually estimated as a percentage. The dataset integrates plot identifiers, location descriptions, geographic coordinates, survey dates, taxonomic information, and taxon-level cover values. It contains 131 taxon rows, of which 129 have at least one recorded occurrence, and 1042 positive taxon-by-plot observations. Taxon richness ranges from 5 to 19 taxa per completed plot, with a median of 10. Data validation included checks of survey status, plot-identifier uniqueness, geographic coordinates, and taxon-cover values. The dataset provides a location-referenced baseline for urban vegetation inventories, descriptive spatial and comparative analyses, teaching, and future location-based comparisons. For reuse, Plot IDs 57 and 66 should be treated as unsurveyed observations rather than as zero-cover vegetation records, and the spatial, seasonal, and taxonomic limitations of the dataset should be considered.

DataVol. 11(11)
Latvia University of Life Sciences and Technologies (LV)
Openalex Percentile: Top 17%
Botany and Plant Ecology Studies
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Georeferenced Plot-Level Data on Urban Grassland Vegetation in Jelgava, Latvia — Inga Grīnfelde, Jovita Pilecka-Uļčugačeva, et al. · Data (2026) | TGRS Research Map | TGRS