arXiv (OAI Expanded)
open access
A Mechanism-Coupled Split Window Network for Medium- to High-Resolution Land Surface Temperature Retrieval
Land surface temperature (LST) is a fundamental physical variable in land-atmosphere interactions, surface energy budgets, and climate processes. LST derived from medium- to high-resolution thermal infrared (TIR) observations effectively reveals thermal environmental disparities across distinct land
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Assessment and enhancement of Landsat 8 land surface temperature retrieval using Mono Window Algorithm and machine learning approaches#201288
- Radiative and Dynamical Controls on the Land-Ocean Warming Contrast in Climate Models#926555
- Integration of Earth Observation Data and Ground-based Measurements to generate High Spatiotemporal Resolution Land Surface Temperature Maps#325708
- A Suite of Models for Producing Synthetic, Small-scale Thermal Imagery of Vegetated Soil Surfaces#640985
- A Suite of Models for Producing Synthetic, Small-scale Thermal Imagery of Vegetated Soil Surfaces#640984
Record · ID 1069672
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive