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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Champion & Seth Species Dataset: AI-Assisted Geocoding and an Interactive WebGIS Search Interface

Authors: Kumar Pandey, Anand; Bhardwaj, Shashank; Blanchflower, Paul; Baldwin, Kiran;

Champion & Seth Species Dataset: AI-Assisted Geocoding and an Interactive WebGIS Search Interface

Abstract

Champion and Seth’s A Revised Survey of the Forest Types of India (1968) remains the most comprehensive classification of Indian forest vegetation, organised into a hierarchical forest type classification comprising bioclimate class, group, and sub-group, with associated floristic lists and distribution descriptions. While the forest type classification has been spatially represented, the species records documented within each forest type exist only in textual form and lack spatial representation. This dataset compiles these species records, which were digitized, geocoded, and structured into a spatially explicit point dataset. Species names were standardized to the World Checklist of Vascular Plants (Govaerts et al. 2026) following scripts adapted from Kindt (2024). Manual verification and correction were applied where automated matching was incomplete or unreliable, particularly for names recorded only at genus level or in abbreviated forms. Each point is attributed with forest type hierarchy, species name as recorded in Champion and Seth, the WCVP-standardized name, distribution description, and the WWF ecoregion within which it falls, assigned through spatial intersection in QGIS. Large Language Models (LLMs) played a central role in accelerating the digitization workflow by converting scanned documents into structured formats, identifying forest type hierarchy from complex descriptive text, extracting species lists embedded in paragraphs, correcting spelling inconsistencies, and expanding abbreviated botanical names. AI also assisted in generating Python scripts used in the QGIS Python console to restructure multi-species records into individual species-specific rows, clean and standardize text fields, assign approximate location coordinates, and build an interactive species search interface. The dataset and associated methodology are described in the accompanying technical manual. An interactive WebGIS interface for searching and exploring species records is available at https://championandsethspecies.pages.dev/. Please refer to the README.txt provided along with the dataset and manual to understand the interface and its features. This dataset represents a complete digitization of species records from Champion and Seth (1968). Any future corrections, taxonomic name updates, or refinements required will be incorporated in future versions of this dataset and reflected in the WebGIS interface.

Keywords

Champion and Seth, Flora, India, Ecoregions, GIS, Species distribution, WebGIS

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average