Accuracy of the Copernicus High-Resolution Layer Forest Type (HRL FTY) assessed with domestic NFI sampling plots in Poland

Marcin Żaczek, Mariusz Walęzak, Anna Olecka, Sylwia Waśniewska, Anna Paczosa
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Abstract

Over the past years, several remote sensing maps of land cover have been produced, but they still exhibit certain differences compared to the real land use that reduce their value for climate and carbon cycle modelling as well as for national estimates of forest carbon stocks and their change. This paper outlines a straightforward framework for evaluating map accuracy and estimating uncertainty in land cover area, specifically for forest-related land cover maps in Poland for the year 2018. The study compares stratified field-based data from the National Forest Inventory (NFI) with remote sensing data on forest variables, at the pixel level, in order to identify suitable methods for accuracy and area uncertainty estimation. Additionally, the paper introduces and presents a variety of accuracy metrics applicable to assess overall uncertainties in GHG inventories. The results indicate that the High-Resolution Layer Forest Type (HRL FTY) product (part of the broader Copernicus Land Monitoring Service [CLMS] portfolio), assessed using NFI field-based information, achieved an overall accuracy (OA) of 69.2%. This metric varies among particular nature protection forms, with the highest observed ones in Natura 2000 sites of 70.45%. The primary source of map errors was associated with distinguishing between broad-leaved and coniferous forest areas. Improving future maps necessitates more precise differentiation between species to better support national forest monitoring systems for the purpose of greenhouse gas (GHG) inventories where information on the spatial distribution and variability of forests sources, biodiversity assessment, threat prevention, estimation of carbon content is becoming an important part of the associated reporting system.
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利用波兰国内 NFI 采样地块评估哥白尼高分辨率层林类型(HRL FTY)的准确性
在过去几年中,已经制作了多幅土地覆被遥感地图,但这些地图与真实的土地利用情况相比仍存在一定差异,从而降低了其在气候和碳循环建模以及国家森林碳储量及其变化估算方面的价值。本文概述了一个评估地图精度和估算土地覆被面积不确定性的直接框架,特别是针对 2018 年波兰与森林相关的土地覆被地图。研究比较了国家森林资源清查(NFI)的分层实地数据和像素级森林变量遥感数据,以确定合适的精度和面积不确定性估算方法。此外,本文还介绍并提出了适用于评估温室气体清单总体不确定性的各种精度指标。结果表明,高分辨率图层森林类型(HRL FTY)产品(更广泛的哥白尼土地监测服务[CLMS]组合的一部分)在使用基于 NFI 的实地信息进行评估后,总体准确度(OA)达到了 69.2%。这一指标因具体的自然保护形式而异,在 Natura 2000 保护区观察到的最高准确率为 70.45%。地图误差的主要来源与区分阔叶林区和针叶林区有关。要改进未来的地图,就必须更精确地区分不同物种,以更好地支持国家森林监测系统,从而进行温室气体(GHG)清单编制,其中有关森林资源的空间分布和可变性、生物多样性评估、威胁预防、碳含量估算等信息正成为相关报告系统的重要组成部分。
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