# Deep learning for urban land use category classification: A review and experimental assessment

*PRI Rank #5 · Topics and Trends in Most Cited Land Use and Ecosystem Services Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/land-use-and-ecosystem-services/2026/rank-5*

| Field | Value |
| --- | --- |
| Rank | #5 |
| 18m citations | 128 |
| Journal | Remote Sensing of Environment |
| Year | 2024 |
| DOI | 10.1016/j.rse.2024.114290 |
| Corresponding authors | Бин Чэн, Bing Xu |
| Institution | The University of Hong Kong, Hong Kong |

**Ranking page:** [Topics and Trends in Most Cited Land Use and Ecosystem Services Papers, Class of 2026](https://pri.pepkio.com/top-papers/land-use-and-ecosystem-services/2026)

**Paper link:** [10.1016/j.rse.2024.114290](https://doi.org/10.1016/j.rse.2024.114290)

## Topics

Urban LULC mapping · deep learning · geospatial big data · Remote sensing · convolutional neural networks · classification units · sample size effects · transfer learning · multi-source data fusion · urban environmental dynamics · land use mapping accuracy · Shenzhen case study · image segmentation · spatial data integration · deep neural network architectures · training data requirements · automated mapping · scale effects

## Cite this ranking

```
Pepkio Research Index (PRI). Topics and Trends in Most Cited Land Use and Ecosystem Services Papers, Class of 2026. https://pri.pepkio.com/top-papers/land-use-and-ecosystem-services/2026. Accessed 2026-10-29.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459
```