← Search

Data · dataset · 2026

Dataset for: Unraveling scale-dependent and non-linear drivers of land surface temperature in a typical arid oasis city

Listed in Teesside University Research Data Repository

This dataset contains the processed geospatial data matrix used for the multi-scale XGBoost-SHAP analysis presented in the manuscript.

Description

It includes seasonal Land Surface Temperature (LST) and corresponding driving factors (e.g., NDVI, NDBI, DEM, NTL, Wind Speed) for Urumqi, China. The data is aggregated at three spatial granularities: 300 m (block scale), 900 m (neighborhood scale), and 1500 m (district scale), covering four seasons from late 2023 to late 2024.

Links

Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 7 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/pmy73xfzgr.119 h agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:social-sciencemapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
licensesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title