Raster Scale Farmland Productivity Assessment with Multi-Source Data Fusion—A Case of Typical Black Soil Region in Northeast China

Bibliographic Details
Title: Raster Scale Farmland Productivity Assessment with Multi-Source Data Fusion—A Case of Typical Black Soil Region in Northeast China
Authors: Yuwen Liu, Chengyuan Wang, Enheng Wang, Xuegang Mao, Yuan Liu, Zhibo Hu
Source: Remote Sensing, Vol 16, Iss 8, p 1435 (2024)
Publisher Information: MDPI AG, 2024.
Publication Year: 2024
Collection: LCC:Science
Subject Terms: soil quality, farmland productivity, indicator system, black soil, Science
More Details: Degradation of black soil areas is a serious threat to national food security and ecological safety; nevertheless, the current lack of information on the location, size, and condition of black soil farmland productivity is a major obstacle to the development of strategies for the sustainable utilization of black soil resources. We synthesized remote sensing data and geospatial thematic data to construct a farmland productivity assessment indicator system to assess the productivity of black soil cropland at the regional scale. Furthermore, we conducted research on the spatial differentiation patterns and a spatial autocorrelation analysis of the assessment results. We found that farmland productivity within this region exhibited a decline pattern from south to north, with superior productivity in the east as opposed to the west, and the distribution follows a “spindle-shaped” pattern. Notably, the Songnen and Sanjiang typical black soil subregions centrally hosted about 46.17% of high-quality farmland and 53.51% of medium-quality farmland, while the Mondong typical black soil subregion in the west predominantly consisted of relatively low-quality farmland productivity. Additionally, farmland productivity displayed a significant positive spatial correlation and spatial clustering, with more pronounced fluctuations in the northeast–southwest direction. The developed indicator system for farmland productivity can illustrate the spatial differentiation and thereby offer a valuable reference for the sustainable management of farmland resources.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2072-4292
Relation: https://www.mdpi.com/2072-4292/16/8/1435; https://doaj.org/toc/2072-4292
DOI: 10.3390/rs16081435
Access URL: https://doaj.org/article/e566e2c14b0e438e8039281a99ed2c75
Accession Number: edsdoj.566e2c14b0e438e8039281a99ed2c75
Database: Directory of Open Access Journals
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More Details
ISSN:20724292
DOI:10.3390/rs16081435
Published in:Remote Sensing
Language:English