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首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >LAND COVER MAPPING, FIRE REGENERATION, AND SCALING STUDIES IN THE CANADIAN BOREAL FOREST WITH 1 KM AVHRR AND LANDSAT TM DATA
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LAND COVER MAPPING, FIRE REGENERATION, AND SCALING STUDIES IN THE CANADIAN BOREAL FOREST WITH 1 KM AVHRR AND LANDSAT TM DATA

机译：利用1 km AVHRR和LANDSAT TM数据对加拿大寒带森林中的土地覆盖图，火灾更新和尺度研究

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摘要

A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km x 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within the wet conifer mosaic. Major differences in the l-km AVHRR and 30-m Landsat TM-derived land cover classes are most likely due to differences in the spatial resolution of the data sets. In general, the 1 km AVHRR land cover classes are vegetation mosaics consisting of mixed combinations of the Landsat classes. Detailed mapping of the global boreal forest with this approach will benefit from algorithms for cloud screening and to atmospherically correct reflectance data for both aerosol and water vapor effects. We believe that this 1 km AVHRR land cover analysis provides new and useful information for regional water, energy, carbon, and trace gases studies in BOREAS, especially given the significant spatial variability in land cover type and associated biophysical land cover parameters (e.g., albedo, leaf area index, FPAR, and surface roughness). Multiresolution land cover comparisons (30 m, 1 km, and 100 km grid cells) also illustrated how heterogeneous landscape patterns are represented in land cover maps with differing spatial scales and provided insights on the requirements and challenges for parameterizing landscape heterogeneity as part of land surface process research. [References: 44]
机译：在加拿大中部的北方森林生态系统中，采用了一种多时相1 km先进的超高分辨率辐射计（AVHRR）土地覆盖分析方法，作为区域土地覆盖测绘，火灾扰动再生和多分辨率土地覆盖比例研究的基础。土地覆被分类是通过使用地面和低空飞机过境的区域野外观测数据进行分析的，以分析光谱-时间集群，该频谱-时间集群是从月均归一化植被指数（NDVI）图像合成物的无监督聚类分析得出的（1992年4月至9月） 。确定了一个821 km x 619 km区域的主要北方森林成分的定量面积比例，范围从南部草原-北方森林过渡带到北部北方过渡森林。北方湿地（主要是低地黑云杉，塔玛拉克，苔藓、,和沼泽）占该地区的33％，而湖泊则占另外13％。旱地针叶落叶林占生态系统的23％。北部湿地针叶树和混交林类别的林分密度的三个水平表明了整个地区的西南偏东北生产力梯度，这通常与区域生长度日的等分一致。在过去的30-35年中，大约30％的地区直接受到火灾的干扰，特别是在加拿大盾构地区，那里大量的火灾再生模式导致了异质的北方景观。从30米Landsat专题测绘仪（TM）数据得出的土地覆盖分类的比对为1 km AVHRR土地覆盖分类的相对精度提供了重要的见解。主要是由于多时相NDVI图像合成过程，所以1 km的AVHRR土地覆盖类别在3-4 km范围内具有有效的空间分辨率，因此，,、沼泽，小水体和小块的千斤顶松树无法解决。湿的针叶树马赛克。由于数据集空间分辨率的差异，最有可能在1公里的AVHRR和30米的Landsat TM得出的土地覆被类别中存在主要差异。通常，1 km AVHRR土地覆盖类别是由Landsat类的混合组合组成的植被镶嵌图。用这种方法对全球北方森林进行详细的测绘，将受益于进行云筛查的算法以及气溶胶和水蒸气效应的大气校正反射率数据。我们认为，这一1 km的AVHRR土地覆盖分析为BOREAS中的区域水，能源，碳和痕量气体研究提供了新的有用信息，特别是考虑到土地覆盖类型和相关生物物理土地覆盖参数（例如反照率）存在很大的空间差异，叶面积指数，FPAR和表面粗糙度）。多分辨率土地覆盖比较（30 m，1 km和100 km网格）还说明了如何在具有不同空间比例的土地覆盖图中表示异质景观格局，并提供了有关将景观异质性参数化为土地表面一部分的要求和挑战的见解过程研究。 [参考：44]

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