摘要
土地覆被是地球科学研究中的重要参量,评价土地覆被数据的制图精度是保障数据合理使用的前提。本文提出了一种基于伪纯像元的精度评价策略(伪纯像元策略),即当低空间分辨率栅格窗口内对应的高空间分辨率数据中优势类别(面积最大的地类)的占比高于伪纯像元纯度阈值(代表像元纯度,取值范围:35%~100%,步长为5%)时,以此栅格窗口为基准生成土地覆被类型为优势类别的伪纯像元用于精度评价。以澜沧江-湄公河(澜湄)流域为试验区,选择GlobeLand30为参考数据,并基于混淆矩阵精度评价方法对比分析了伪纯像元策略与重采样法(最近邻法和众数法)在CCI-LC(300 m)和MCD12Q1(500 m)2套全球土地覆被数据精度评价中的差异。结果表明:(1)伪纯像元策略在35%~100%纯度阈值下对CCI-LC和MCD12Q1在澜湄流域评价的精度分别为72.76%~55.26%和71.44%~45.41%,比重采样法评价的单一精度(众数法:71.21%和70.54%、最近邻法:71.48和69.87%)能更好地反映像元纯度对土地覆被数据精度的影响;(2)CCI-LC的总体精度高于MCD12Q1,且2套数据的精度差随纯度阈值的增大而增加,CCI-LC和MCD12Q1在35%、100%纯度阈值下的精度差分别为1.32%和9.85%;(3)2套数据中耕地、有林地、草地和水体的分类精度均相对较高,而灌木林地(精度接近0)和裸地的分类精度均较低;(4)2套数据与GlobeLand30的空间不一致区域多出现在土地覆被类型高度异质化的混合像元区域,且随纯度阈值的增大,评价样本栅格更趋均质,混合像元对评价精度的影响也会递减。伪纯像元精度评价策略适用于跨空间分辨率土地覆被数据的精度对比,为评价全球土地覆被产品在区域尺度的适用性及适用范围提供了新的检验策略。
Land cover is an important parameter in geoscience research,and the accuracy assessment of land cover products is a prerequisite to ensure reasonable application of land cover products.In this study,an accuracy assessment strategy based on pseudo-pure pixels(i.e.,pseudo-pure pixel strategy)is proposed.That is,calculating the area of land cover types of the high-resolution pixels within a pixel window of coarse spatial resolution data and defining the land cover type with the largest area as the advantage type,and then generating pseudo-pure pixels of advantage type based on the pixel window when the area proportion of the advantage type is higher than a pseudo-pure pixel purity threshold(ranging from 35%to 100%,with a step length of 5%).We take the Lancang-Mekong(Lanmei)basin as the study area and select the GlobeLand30 as the reference data.The confusion matrix accuracy assessment method was used to compare the difference in the accuracy of two sets of global land cover data,i.e.,CCI-LC(300 m)and MCD12Q1(500 m),using different assessment methods,i.e.,the pseudo-pure pixel strategy and the resampling method(Nearest and Majority).Our results show that:(1)The accuracy using the pseudo-pure pixel strategy for CCI-LC and MCD12Q1 in the Lanmei Basin under the purity thresholds of 35%~100%are 72.76%~55.26%and 71.44%~45.41%,respectively,and it can better reflect the influence of pixel purity on the accuracy of land cover data than the single accuracy obtained by resampling method(Nearest:71.21%and 70.54%;Majority:71.48 and 69.87%);(2)The overall accuracy of CCI-LC is higher than that of MCD12Q1.The accuracy difference of the two datasets increases with the increase of purity threshold,and it is 1.32%and 9.85%respectively for purity threshold of 35%and 100%,respectively;(3)In both datasets,the classification accuracy of cropland,forest,grassland,and water is relatively high,and the classification accuracy of shrub land and bare land is relatively low;(4)The spatial inconsistency between the two datasets and the GlobeLand30 mainly occur in mixed pixel regions with highly heterogeneous land cover types.And the assessment sample grids are purer with the increase of pseudo-pure pixel threshold,which reduces the effects of mixed pixels on accuracy assessment.The pseudo-pure pixel strategy has the potential to compare the mapping accuracy of land cover data with different spatial resolutions,and provides a promising validation method for determining the applicability and application scope of global land cover products at regional scales.
作者
徐肖
李娅婷
樊辉
XU Xiao;LI Yating;FAN Hui(Institute of International Rivers and Eco-Security,Yunnan University,Kunming,650091,China;Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security,Kunming 650091,China)
出处
《地球信息科学学报》
CSCD
北大核心
2022年第8期1617-1630,共14页
Journal of Geo-information Science
基金
第二次青藏高原综合科学考察研究(2019QZKK0402)
国家自然科学基金项目(41971239、41461017)
云南省教育厅科学研究基金项目(2022Y061)。
