加拿大卫星森林资源调查 (SBFI) 卫星森林资源清查(SBFI)提供了 2020 年加拿大森林覆盖、干扰恢复、结构、物种和林分年龄的信息,以及 1985-2020 年林分替代干扰的信息。SBFI 多边形代表了与战略森林资源清查中划定的林分相似的同质森林状况。使用多分辨率分割算法对 2020 年大地遥感卫星表面反射 BAP 复合影像(30 米空间分辨率)、火灾年份和采伐年份图层进行了划分。最小地图单位为 0.45 公顷(5 像素),用于定义多边形。使用相同的数据、属性和时间表示法绘制了加拿大全部森林生态系统的地图,从而形成了加拿大约 6.5 亿公顷森林生态系统的通用植被清查系统。鉴于加拿大森林面积大且种类繁多,SBFI 的优势在于使用一致的数据源和方法,跨越管辖边界、管理和非管理林区,从而能够一致地生成综合、空间明确的信息输出。此处包含的数据基于免费开放的卫星数据和信息产品,并遵循既定的交流方法。前言 – 人工智能教程
卫星数据越来越多地用于提供信息,以支持不同详细程度、各种属性和空间范围的森林监测和报告。森林是一种动态环境,定期评估有利于捕捉局部和大面积的状况和变化。卫星数据可定期(如每年)提供与森林科学和管理相关的产品,包括土地覆盖、干扰(即日期、范围、严重程度和类型)、森林恢复(如干扰后树木回归的量化)和森林结构(如体积、生物量、冠层覆盖、林分高度),并以系统、透明和可重复的方式生成大面积的产品。虽然基于卫星数据输入的典型结果是基于像素的,但许多最终用户仍然需要基于多边形的森林资源信息。为了满足这一信息需求,并为森林资源清查属性(如树种组合)提供空间背景,我们提出了一种新的工作流程,在加拿大应用图像分割方法生成空间上独特的林分(多边形),这是管理级清查的基本空间单位,从而生成空间上明确的林分级卫星森林资源清查(SBFI)。
因此,SBFI 为汇总和归纳其他基于像素的森林数据集提供了空间背景。加拿大开发了一个国家陆地生态系统监测系统 (NTEMS),该系统利用中等空间分辨率的图像(主要来自 Landsat),每年以像素为单位描述加拿大从 1984 年至今的森林特征。这些 NTEMS 数据集用于为 SBFI 多边形区域填充状态信息(如当前的土地覆被类型、主要树种或总生物量)以及动态信息(如该多边形区域是否发生过变化、何时发生变化、发生了哪些变化,如果发生了变化,森林是如何恢复的)。在此,我们概述了森林监测的信息驱动因素,介绍了一套旨在满足这些信息需求的产品,并随后在加拿大以森林为主的生态系统的 650 兆公顷范围内展示了 SBFI 概念。在此过程中,使用相同的数据、属性和时间表示法绘制了整个加拿大森林生态系统(管理的和未管理的)的地图。此外,使用多边形还可以生成树种组成、总生物量和木材体积等属性,这些属性采用景观管理者熟悉的林分尺度格式,适合战略规划。这里介绍的数据、方法和结果可移植到其他地区和输入数据源,加拿大的国家 SBFI 结果可通过开放获取。
有关地物属性的完整描述,请参见所附的数据字典或此处的可下载数据集。
CA SBFI feature attributes
https://opendata.nfis.org/downloads/forest_change/CA_Forest_Satellite_Based_Inventory_2020.zip
Group | Field | Description | Units |
---|---|---|---|
ID | ID | Unique polygon identifier | |
TILE | Tile identifier | ||
Geometry | AREA_HA | Area of the polygon | ha |
PERIMETER_M | Length of polygon’s boundary | m | |
Stratification | JURSDICTION | Most represented province/territory | |
ECOZONE | Most represented terrestrial ecozone as defined by Ecological Stratification Working Group (1996) | ||
ECOPROVINCE | Most represented ecoprovince as defined by Ecological Stratification Working Group (1996) | ||
ECOREGION | Most represented ecoregion as defined by Ecological Stratification Working Group (1996) | ||
MANAGEMENT | Most represented land status from the forest management classification from Stinson et al_ (2019) | ||
Land cover | LC_WATER | Area covered by water | % of polygon area |
LC_SNOW_ICE | Area covered by snow/ice | % of polygon area | |
LC_ROCK_RUBBLE | Area covered by rock/rubble | % of polygon area | |
LC_EXPOSED_BARREN | Area covered by exposed/barren land | % of polygon area | |
LC_BRYOIDS | Area covered by bryoids | % of polygon area | |
LC_SHRUBS | Area covered by shrubs | % of polygon area | |
LC_WETLAND | Area covered by wetland | % of polygon area | |
LC_WETLAND-TREED | Area covered by wetland-treed | % of polygon area | |
LC_HERBS | Area covered by herbs | % of polygon area | |
LC_CONIFEROUS | Area covered by coniferous | % of polygon area | |
LC_BROADLEAF | Area covered by broadleaf | % of polygon area | |
LC_MIXEDWOOD | Area covered by mixedwood | % of polygon area | |
LC_TREED | Area covered by treed vegetation derived from combining the land cover classes | % of polygon area | |
LC_FAO_FOREST | Area covered by forest consistent with FAO definitions (Wulder et al_ 2020) | % of polygon area | |
LC_WETLAND_VEGETATION | Area covered by wetlands derived from combining the land cover classes | % of polygon area | |
Disturbances | DISTURB_FIRE_PERC | Area impacted by fire disturbances | % of polygon area |
DISTURB_FIRE_YEAR | Modal year of fire disturbances | years | |
DISTURB_FIRE_MAGNITUDE_MIN | Minimum value of fire magnitude | dNBR | |
DISTURB_FIRE_MAGNITUDE_MAX | Maximum value of fire magnitude | dNBR | |
DISTURB_FIRE_MAGNITUDE_AVG | Average value of fire magnitude | dNBR | |
DISTURB_FIRE_MAGNITUDE_SD | Standard deviation of fire magnitude | dNBR | |
DISTURB_FIRE_MAGNITUDE_MED | Median value of fire magnitude | dNBR | |
DISTURB_HARVEST_PERC | Area impacted by harvesting disturbances | % of polygon area | |
DISTURB_HARVEST_YEAR | Modal year of harvesting disturbances | years | |
Recovery | RECOVERY_FIRE_MIN | Minimum value of spectral recovery for fire disturbances | % of pre-disturbance |
RECOVERY_FIRE_MAX | Maximum value of spectral recovery for fire disturbances | % of pre-disturbance | |
RECOVERY_FIRE_AVG | Average value of spectral recovery for fire disturbances | % of pre-disturbance | |
RECOVERY_FIRE_SD | Standard deviation of spectral recovery for fire disturbances | % of pre-disturbance | |
RECOVERY_FIRE_MED | Median value of spectral recovery for fire disturbances | % of pre-disturbance | |
RECOVERY_HARVEST_MIN | Minimum value of spectral recovery for harvesting disturbances | % of pre-disturbance | |
RECOVERY_HARVEST_MAX | Maximum value of spectral recovery for harvesting disturbances | % of pre-disturbance | |
RECOVERY_HARVEST_AVG | Average value of spectral recovery for harvesting disturbances | % of pre-disturbance | |
RECOVERY_HARVEST_SD | Standard deviation of spectral recovery for harvesting disturbances | % of pre-disturbance | |
RECOVERY_HARVEST_MED | Median value of spectral recovery for harvesting disturbances | % of pre-disturbance | |
Age | AGE_MIN | Minimum forest age | years |
AGE_MAX | Maximum forest age | years | |
AGE_AVG | Average forest age | years | |
AGE_SD | Standard deviation of forest age | years | |
AGE_MED | Median forest age | years | |
AGE_0_10, AGE_10_20, AGE_20_30, AGE_30_40, AGE_40_50, AGE_50_60, AGE_60_70, AGE_70_80, AGE_80_90, AGE_90_100, AGE_100_110, AGE_110_120, AGE_120_130, AGE_130_140, AGE_140_150, AGE_GT_150 | Ten-year age class frequency distribution | % of treed area in polygon | |
Forest structure | STRUCTURE_CANOPY_HEIGHT_MIN | Minimum canopy height | m |
STRUCTURE_CANOPY_HEIGHT_MAX | Maximum canopy height | m | |
STRUCTURE_CANOPY_HEIGHT_AVG | Average canopy height | m | |
STRUCTURE_CANOPY_HEIGHT_SD | Standard deviation of canopy height | m | |
STRUCTURE_CANOPY_HEIGHT_MED | Median canopy height | m | |
STRUCTURE_CANOPY_COVER_MIN | Minimum canopy cover | % | |
STRUCTURE_CANOPY_COVER_MAX | Maximum canopy cover | % | |
STRUCTURE_CANOPY_COVER_AVG | Average canopy cover | % | |
STRUCTURE_CANOPY_COVER_SD | Standard deviation of canopy cover | % | |
STRUCTURE_CANOPY_COVER_MED | Median canopy cover | % | |
STRUCTURE_LOREYS_HEIGHT_MIN | Minimum Lorey’s height | m | |
STRUCTURE_LOREYS_HEIGHT_MAX | Maximum Lorey’s height | m | |
STRUCTURE_LOREYS_HEIGHT_AVG | Average Lorey’s height | m | |
STRUCTURE_LOREYS_HEIGHT_SD | Standard deviation of Lorey’s height | m | |
STRUCTURE_LOREYS_HEIGHT_MED | Median Lorey’s height | m | |
STRUCTURE_BASAL_AREA_MIN | Minimum basal area | m2 ha−1 | |
STRUCTURE_BASAL_AREA_MAX | Maximum basal area | m2 ha−1 | |
STRUCTURE_BASAL_AREA_AVG | Average basal area | m2 ha−1 | |
STRUCTURE_BASAL_AREA_SD | Standard deviation of basal area | m2 ha−1 | |
STRUCTURE_BASAL_AREA_MED | Median basal area | m2 ha−1 | |
STRUCTURE_BASAL_AREA_TOTAL | Total basal area in polygon | m2 | |
STRUCTURE_AGB_MIN | Minimum aboveground biomass | t ha−1 | |
STRUCTURE_AGB_MAX | Maximum aboveground biomass | t ha−1 | |
STRUCTURE_AGB_AVG | Average aboveground biomass | t ha−1 | |
STRUCTURE_AGB_SD | Standard deviation of aboveground biomass | t ha−1 | |
STRUCTURE_AGB_MED | Median aboveground biomass | t ha−1 | |
STRUCTURE_AGB_TOTAL | Total aboveground biomass in polygon | t | |
STRUCTURE_VOLUME_MIN | Minimum gross stem volume | m3 ha−1 | |
STRUCTURE_VOLUME_MAX | Maximum gross stem volume | m3 ha−1 | |
STRUCTURE_VOLUME_AVG | Average gross stem volume | m3 ha−1 | |
STRUCTURE_VOLUME_SD | Standard deviation of gross stem volume | m3 ha−1 | |
STRUCTURE_VOLUME_MED | Median gross stem volume | m3 ha−1 | |
STRUCTURE_VOLUME_TOTAL | Total gross stem volume in polygon | m3 | |
Tree species | SPECIES_NUMBER | ||
SPECIES_1 | Name of the 1st most common leading tree species representing a percentage of treed area in polygon >2_5% | ||
SPECIES_2 | Name of the 2nd most common leading tree species representing a percentage of treed area in polygon >2_5% | ||
SPECIES_3 | Name of the 3rd most common leading tree species representing a percentage of treed area in polygon >2_5% | ||
SPECIES_4 | Name of the 4th most common leading tree species representing a percentage of treed area in polygon >2_5% | ||
SPECIES_5 | Name of the 5th most common leading tree species representing a percentage of treed area in polygon >2_5% | ||
SPECIES_1_PERC | Area covered by the 1st most common leading tree species | % of treed area in polygon | |
SPECIES_2_PERC | Area covered by the 2nd most common leading tree species | % of treed area in polygon | |
SPECIES_3_PERC | Area covered by the 3rd most common leading tree species | % of treed area in polygon | |
SPECIES_5_PERC | Area covered by the 5th most common leading tree species | % of treed area in polygon | |
SPECIES_CONIFEROUS_PERC | Area covered by coniferous tree species | % of treed area in polygon | |
SPECIES_CML1 | Name of the 1st most common tree species based on the class membership likelihood values | ||
SPECIES_CML2 | Name of the 2nd most common tree species based on the class membership likelihood values | ||
SPECIES_CML3 | Name of the 3rd most common tree species based on the class membership likelihood values | ||
SPECIES_CML4 | Name of the 4th most common tree species based on the class membership likelihood values | ||
SPECIES_CML5 | Name of the 5th most common tree species based on the class membership likelihood values | ||
SPECIES_CML1_PERC | Distribution of the class membership likelihood values of the 1st most common tree species | % of class membership likelihood from treed pixels in polygon | |
SPECIES_CML2_PERC | Distribution of the class membership likelihood values of the 2nd most common tree species | % of class membership likelihood from treed pixels in polygon | |
SPECIES_CML3_PERC | Distribution of the class membership likelihood values of the 3rd most common tree species | % of class membership likelihood from treed pixels in polygon | |
SPECIES_CML4_PERC | Distribution of the class membership likelihood values of the 4th most common tree species | % of class membership likelihood from treed pixels in polygon | |
SPECIES_CML5_PERC | Distribution of the class membership likelihood values of the 5th most common tree species | % of class membership likelihood from treed pixels in polygon | |
SPECIES_CML_CONIFEROUS_PERC | Proportion of class membership likelihood values of coniferous tree species | % of class membership likelihood from treed pixels in polygon | |
SPECIES_CML_ASSEMBLAGES | Name of the tree species conforming an assemblage | ||
SPECIES_CML_ASSEMBLAGES_PERC | Proportion of class membership likelihood values conforming the assemblage | % of class membership likelihood from treed pixels in polygon | |
Symbology | SYMB_LAND_BASE_LEVEL | Land base level classification based on the NFI land cover hierarchy (Wulder et al_ 2008) | |
SYMB_LAND_COVER_LEVEL | Land cover level classification based on the NFI land cover hierarchy (Wulder et al_ 2008) | ||
SYMB_VEGETATION_LEVEL | Vegetation level classification based on the NFI land cover hierarchy (Wulder et al_ 2008) | ||
SYMB_DISTURBANCE | Simplified coding for disturbance type and year | ||
SYMB_RECOVERY | Simplified coding for spectral recovery | ||
SYMB_AGE | Simplified coding for forest age |
数据集后处理
为便于使用,瓦片数据集被合并为一个单一的特征集合。网格文件保留原样,以便用户了解网格是如何创建的。
引用
代码语言:javascript复制Wulder, Michael A., Txomin Hermosilla, Joanne C. White, Christopher W. Bater, Geordie Hobart, and Spencer C. Bronson. "Development and
implementation of a stand-level satellite-based forest inventory for Canada." Forestry: An International Journal of Forest Research (2024): cpad065.
数据引用
代码语言:javascript复制Wulder, M.A., Hermosilla, T., White, J.C., Bater, C.W., Hobart, G., Bronson, S.C., 2024. Development and implementation of a stand-level
satellite-based forest inventory for Canada. Forestry: An International Journal of Forest Research. https://doi.org/10.1093/forestry/cpad065
代码
代码语言:javascript复制var sbfi_merged = ee.FeatureCollection("projects/sat-io/open-datasets/CA_FOREST/CA_SBFI/CA_SBFI_MERGED");
var grid_fe = ee.FeatureCollection("projects/sat-io/open-datasets/CA_FOREST/CA_SBFI/GRID_forested_ecosystems");
License¶
This work is licensed under and freely available to the public under the Open Government Licence - Canada.
Created by: Wulder et al. 2024
Curated in GEE by : Samapriya Roy
Keyworks: Landsat, land cover, change detection, forest structure, biomass; NFI
Last updated in GEE: 2024-02-22