多源土地利用产品在黄土丘陵沟壑区的精度评估
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中国科学院生态环境研究中心城市与区域生态国家重点实验室

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TP79

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国家自然科学(U21A2011;41971129),国家重点研发计划课题(2022YFF1300403)。


Accuracy assessment of multi-source land use products in the loess hilly and gully region
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State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences

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    摘要:

    多源土地利用产品精度评估对于获取可靠地表信息、支持土地规划和管理、促进区域生态保护与高质量发展等至关重要。然而,现有的土地利用产品能否准确刻画复杂地形或破碎生境(如黄土丘陵沟壑区)的地表覆盖特征尚未可知。本研究以黄河二级支流关川河流域(Guanchuan River Basin)为例,基于高精度GCLUCC土地利用数据,从空间分布、面积一致性和空间一致性三个方面评估了空间分辨率为10米和30米的6种土地利用产品(WorldCover 10 m、ESRI 10m、GLC_FCS30-2020、GlobleLand30、CNLUCC和CLCD)在黄土丘陵沟壑区的准确性。GCLUCC是基于GF-2(0.8m)、DEM(5m)和6400个野外采样点,借助面向对象法和人工目视解译获得,整体精度大于95%。评估结果显示:(i)在分类特征方面,大部分产品均能提取主要的土地类别,但提取效率和准确度存在明显差异,特别是在梯田、林地和建设用地等地类的空间分布上;(ii)在面积一致性上,各产品与GCLUCC在各地类的面积上均存在显著差异。例如,部分产品的草地面积是GCLUCC的2倍以上,而林地和水域面积仅占GCLUCC的0.13%-12.11%和1.41%-11.27%。(iii)在整体精度上,GlobleLand30和WorldCover 10m展现了相对较高的精度,分别达到58.21%和50.19%。而CLCD和CNLUCC的准确性相对较低,其中林地与草地、梯田与草地以及建设用地与梯田之间的分类混淆显著。(iv)各产品间以及与实际地表间的空间误差显著,特别是对乔木、灌木、裸地和水体的分类准确性存在重大挑战。综上所述,当前土地利用产品在精确描述黄土丘陵沟壑区的地表覆盖特征方面仍存在明显的挑战。未来的产品开发应更多地考虑地形和地理特征,并加强对特定土地利用类型,如乔木、灌木、裸地和水体的识别,以增强数据的准确性和决策的可靠性。

    Abstract:

    Evaluating the accuracy of multi-source land use products is essential for obtaining reliable surface information, supporting land planning and management, and promoting regional ecological protection and high-quality development. However, the capability of existing land use products to accurately depict the surface cover characteristics in complex terrains or fragmented habitats, such as the loess plateau hilly and gully regions, remains uncertain. Taking the Guanchuan River Basin, a secondary tributary of the Yellow River, as an example, this study assessed the accuracy of six land use products with spatial resolutions of 10 m and 30 m (WorldCover 10 m, ESRI 10m, GLC_FCS30-2020, GlobleLand30, CNLUCC, and CLCD) in the loess hilly and gully region using high-precision GCLUCC land use data. This GCLUCC data, with an overall accuracy exceeding 95%, was derived from GF-2 (0.8m), DEM (5m), and 6400 field sampling points, employing the object-oriented method and manual visual interpretation. The evaluation results showed that (i) In terms of classification characteristics, most products could extract main land categories, yet significant differences existed in extraction efficiency and accuracy, especially regarding the spatial distribution of terraced fields, forest lands, and construction lands; (ii) For area consistency, there were significant discrepancies in land category areas between various products and GCLUCC. For instance, the grassland area in some products was more than twice that of GCLUCC, while forest and water areas accounted for only 0.13%-12.11% and 1.03%-5.86% of GCLUCC, respectively; (iii) In terms of overall accuracy, GlobleLand30 and WorldCover 10m demonstrated relatively higher accuracy, reaching 58.21% and 50.19%, respectively. The accuracy of CLCD and CNLUCC was comparatively lower, with notable classification confusion between forests and grasslands, terraced fields and grasslands, and construction lands and terraced fields; (iv) Significant spatial discrepancies existed between various products and the actual ground surface, particularly in accurately classifying forests, shrubs, bare land, and water bodies. In conclusion, current land use products still face notable challenges in precisely describing surface cover characteristics in the loess plateau hilly and gully regions. Future product development should place greater emphasis on topographical and geographical features and strengthen the recognition of specific land use types like forests, shrubs, bare land, and water bodies to enhance data accuracy and decision-making reliability.

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  • 收稿日期:2023-10-31
  • 最后修改日期:2023-12-25
  • 录用日期:2023-12-27
  • 在线发布日期: 2024-04-29
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