Data · dataset · 2026
Dataset Associated with “Construction and Application of a Three-Dimensional Recreation Opportunity Spectrum in the Tangjiahe Area of Giant Panda National Park”
Listed in ScienceDB
This dataset is the spatial achievement data formed by the three-dimensional recreation opportunity spectrum (Tri ROS) study of Tangjiahe Park in Giant Panda National Park.
Description
The data is generated through steps such as multi-source spatial data preprocessing, indicator calculation, hexagonal grid summary, rule classification, and spatial optimization. The spatial scope is Tangjiahe Park, which belongs to the cross-sectional data during the research period and does not involve continuous time series. The dataset includes the final classification results, median, mean, and natural breakpoint method thresholds for Tri ROS, as well as Tri ROS classification results at hexagonal grid scales of 400, 545, and 700 meters, and traditional continuous spectrum control ROS results.
The data is in Shapefile (. shp) format, with spatial units recorded as surface features. The attribute table mainly includes fields such as grid number, recreation opportunity type code, type name, and related classification results. The data adopts the CGCS2000 coordinate system, and the measurement units of spatial distance and area are consistent with the projection units of this coordinate system. The effective grids involved in classification within the research area have completed indicator calculation and type assignment, and there are no missing records caused by data loss; The areas outside the research area and the cropped boundaries are not considered missing data.
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The results of different thresholds and grid scales are mainly used for model sensitivity analysis and should not be directly combined for statistical analysis. The data does not include personal information of tourists or raw locations of sensitive species that have not been processed. The Tri ROS results reflect potential recreational opportunities and their management contexts, and do not directly represent actual tourist flow, ecological impacts that have occurred, or statutory functional zoning.
The data can be read and analyzed using GIS software such as ArcGIS, ArcGIS Pro, or QGIS.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.43470 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Geoinformatics 71% · Tabular 65%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.43470 | 8 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3704 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (71%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:tabular | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |