An ensemble learning-based approach for large-scale cultivated land quality monitoring

Dan Liu, Chenglong Yu, Rui Feng and Shiping Yin

Ecological Modelling, 2025, vol. 508, issue C

Abstract: Cultivated land quality is the foundation of agricultural production, directly affecting food security and the stability of the ecological environment. Based on MODIS remote sensing data, the Harmonized World Soil Database (HWSD), terrain information, and other data, combined with GBDT and Bagging ensemble learning algorithms, this study investigates the mapping and validating of cultivated land quality in Northeast China, exploring the feasibility of assessing cultivated land quality in this region using remote sensing data. The results show that over 95 % of the cultivated land in Northeast China has high quality, and remote sensing technology demonstrates high accuracy in identifying high-quality land. However, notable limitations exist in assessing low-quality croplands, with remote sensing detecting substantially lower proportions of Grade 3 croplands (0.50–0.60 %) relative to GIS-derived results (1.24–4.56 %). the assessment of low-quality land has certain limitations, mainly due to the insufficient capability of remote sensing data in identifying complex soil types and low-quality cultivated land. This study provides a new technical approach and theoretical support for cultivated land quality monitoring.

Keywords: Ensemble learning; Remote sensing; GIS; Cultivated land quality; Northeast China (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380025001802
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:508:y:2025:i:c:s0304380025001802

DOI: 10.1016/j.ecolmodel.2025.111195

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().