Evaluation and fusion of global 10 m land cover data in first batch of Chinese wetland cities

YIN Xiaogan; JIANG Weiguo; LING Ziyan; WANG Xiaoya; DENG Yawen

doi:10.11834/jrs.20233058

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Evaluation and fusion of global 10 m land cover data in first batch of Chinese wetland cities
Vol. 27, Issue 6, Pages: 1334-1347(2023)
Received：01 March 2023，

Published：07 June 2023
DOI： 10.11834/jrs.20233058
稿件说明：

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尹潇淦，蒋卫国，凌子燕，王晓雅，邓雅文.2023.全球10 m土地覆盖数据在中国首批国际湿地城市的评价与融合.遥感学报，27（6）： 1334-1347 DOI： 10.11834/jrs.20233058.

Yin X G，Jiang W G，Ling Z Y，Wang X Y and Deng Y W. 2023. Evaluation and fusion of global 10 m land cover data in first batch of Chinese wetland cities. National Remote Sensing Bulletin， 27（6）：1334-1347 DOI： 10.11834/jrs.20233058.

摘要

高精度的土地覆盖数据是生态系统监测评估与区域可持续发展的重要研究基础，然而目前较少有研究对较高分辨率土地覆盖数据（10 m）在城市尺度的区域上进行研究。随着国际湿地城市的建立，也需要高质量高精度的土地覆盖数据为相关研究提供信息。本文以中国首批国际湿地城市为研究区，对3套全球10 m土地覆盖数据DW（Dynamic World）、ESA（ESA WorldCover）、ESRI（Esri Land Cover））选择2020年和2021年进行空间一致性分析和精度评价，最后提出基于空间一致性分析与精度评价的融合方法，基于空间一致性分析结果和精度评价结果进行土地覆盖数据集融合以重建生产一套新数据。结果表明：（1）任何两个数据集之间，水体、林地、耕地、建设用地这些类型一致度比较高，而湿地、草地和裸地混淆度比较高。（2）ESRI与DW的空间一致性程度最高，全部一致区域占比最高（60%以上），全部不一致区域占比最低（6%以下）且多分布在沿海沿江，湿地广布的区域，这些区域异质性强，土地覆盖类型复杂。（3）ESA的总体精度最高，DW和ESRI的总体精度较为接近；ESA的湿地类型的精度和分类细节程度相对较高，更适用于城市湿地相关研究。（4）基于空间一致性分析与精度评价的融合方法可以有效融合多源土地覆盖数据，提高具有广泛异质区域数据的精度；本文融合结果的总体精度（80%以上）和Kappa系数均高于3套原数据，可以为国际湿地城市认证及相关研究提供数据支撑。

Abstract

High-precision land cover data are an important research basis for ecosystem monitoring and assessment and regional sustainable development. However

studies on high-resolution land cover data (10 m) at the urban scale are few. With the establishment of wetland cities

high-quality and high-precision land cover data have become essential to provide information for relevant research.

Taking the first wetland cities in China

as the study area

this study selected three sets of global 10 m land cover data (Dynamic World

ESA WorldCover

and Esri Land Cover) in 2020 and 2021

for spatial consistency evaluation and precision evaluation. First

the consistency and confusion between any two sets of data were calculated using the spatial superposition method

and a spatial consistency distribution map was drawn to analyze the spatial consistency of the three sets of data. Second

the confusion matrix was calculated by constructing verification sample points through visual interpretation to evaluate the accuracy of the three sets of data. Finally

based on the results of the spatial consistency analysis and accuracy evaluation

the land cover data sets were fused to produce a new set of data

and a fusion method based on spatial consistency analysis and accuracy evaluation was proposed.

Results showed that (1) in any two data sets

the consistency of the water

forest

cropland

and urban areas was high

whereas the confusion of the wetland

grassland

and bare areas was high

and (2) the spatial consistency between ESRI and DW was the highest

with the highest proportion of consistent areas (more than 60%) and lowest proportion of inconsistent areas (less than 6%)

which were distributed mainly in areas along the coast and rivers and with extensive wetlands. Such areas had strong heterogeneity and complex land cover types. (3) ESA had the highest overall accuracy

whereas DW and ESRI had a similar overall accuracy. The ESA wetland types had relatively high precision and classification details

which are suitable for urban wetland-related research. (4) Multisource land cover data can be effectively integrated

and the data accuracy of widely heterogeneous regions can be improved using the fusion method based on spatial consistency analysis and accuracy evaluation. The overall accuracy of the fusion results (more than 80%) and kappa coefficient was higher than that of the three original data.

Therefore

the research results can provide data support and auxiliary decision-making support for wetland city certification and related research.

关键词

Keywords

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