Spatial patterns of biomass change across Finland in 2009–2015

Markus Haakana, Sakari Tuominen, Juha Heikkinen, Mikko Peltoniemi, Aleksi Lehtonen
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Abstract

Forest characteristics vary largely at the regional level and in smaller geographic areas in Finland. The amount of greenhouse gas emissions is related to changes in biomass and the soil type (e.g. upland soils vs. peatlands). In this paper, estimating and explaining spatial patterns of tree biomass change across Finland was the main interest. We analysed biomass changes on different soil and site types between the years 2009 and 2015 using the Finnish multi-source national forest inventory (MS-NFI) raster layers. MS-NFI method is based on combining information from satellite imagery, digital maps and national forest inventory (NFI) field data. Automatic segmentation was used to create silvicultural management and treatment units. An average biomass estimate of the segmented MS-NFI (MS–NFI–seg) map was 73.9 tons ha−1 compared to the national forest inventory estimate of 76.5 tons ha−1 in 2015. Forest soil type had a similar effect on average biomass in MS–NFI–seg and NFI data. Despite good regional and country-level results, segmentation narrowed the biomass distributions. Hence, biomass changes on segments can be considered only approximate values; also, those small differences in average biomass may accumulate when map layers from more than one time point are compared. A kappa of 0.44 was achieved for precision when comparing undisturbed and disturbed forest stands in the segmented Global Forest Change data (GFC-seg) and MS–NFI–seg map. Compared to NFI, 69% and 62% of disturbed areas were detected by GFC-seg and MS–NFI–seg, respectively. Spatially accurate map data of biomass changes on forest land improve the ability to suggest optimal management alternatives for any patch of land, e.g. in terms of climate change mitigation.

2009-2015年芬兰生物量变化空间格局
芬兰的森林特征在区域一级和较小的地理区域差异很大。温室气体排放量与生物量和土壤类型的变化有关(例如高地土壤与泥炭地)。在本文中,估计和解释芬兰树木生物量变化的空间模式是主要的兴趣。我们使用芬兰多源国家森林目录(MS-NFI)光栅层分析了2009年至2015年间不同土壤和场地类型的生物量变化。MS-NFI方法是基于结合卫星图像、数字地图和国家森林调查(NFI)实地数据的信息。自动分割用于创建造林管理和处理单元。分段MS-NFI(MS–NFI–seg)图的平均生物量估计为73.9吨ha−1,而2015年的国家森林存量估计为76.5吨ha−1。在MS–NFI–seg和NFI数据中,森林土壤类型对平均生物量的影响相似。尽管在区域和国家层面取得了良好的结果,但细分缩小了生物量的分布。因此,分段上的生物量变化只能被视为近似值;此外,当比较来自一个以上时间点的地图层时,平均生物量的这些微小差异可能会累积。在分段的全球森林变化数据(GFC seg)和MS–NFI–seg图中,当比较未受干扰和受干扰的林分时,精度达到了0.44的kappa。与NFI相比,GFC seg和MS–NFI–seg分别检测到69%和62%的干扰区域。林地生物量变化的空间精确地图数据提高了为任何一块土地提出最佳管理替代方案的能力,例如在减缓气候变化方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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