Land Cover Vulnerability Change 2050 - Country

Use this country model layer when performing analysis within a single country. This layer displays predictions within each country of relative vulnerability to modification by humans by the year 2050. ESA CCI land cover maps from the years 2010 and 2018 were used to create these predictions. Variable mapped: Vulnerability of land cover to anthropogenic change by 2050. Data Projection: Cylindrical Equal Area Mosaic Projection: Cylindrical Equal Area Extent: Global Cell Size: 300m Source Type: Thematic Visible Scale: 1:50,000 and smaller Source: Clark University Publication date: April 2021 Analysis: Analysis-Optimized What you can do with this layer? This layer can be used in analysis, to estimate and compare vulnerability to land cover change globally due to expansion of human activity, by 2050. This layer is useful in ecological planning, helping to prioritize areas for conservation. Analysis In order to leverage the optimization for analysis, the capability must be enabled by your ArcGIS organization administrator. More information on enabling this feature can be found in the ‘Regional data hosting’ section of this help doc. Optimized for analysis means this layer does not have size constraints for analysis and it is recommended for multisource analysis with other layers optimized for analysis. See the ArcGIS Living Atlas: Analysis-Optimized Imagery Layers Group for a complete list of imagery layers optimized for analysis. Links to the six Clark University land cover 2050 layers in ArcGIS Living Atlas of the World: There are three scales (country, regional, and global) for the land cover and vulnerability models. They’re all slightly different since the country model can be more fine-tuned to the drivers in that particular area. Regional (continental) and global have more spatially consistent model weights. Which should you use? If you’re analyzing one country or want to make accurate comparisons between proximate countries, use the country level. If mapping larger patterns or vastly separated countries, use the global or regional extent (depending on your area of interest). Land Cover 2050 - Global Land Cover 2050 - Regional Land Cover 2050 - Country Land Cover Vulnerability to Change 2050 Global Land Cover Vulnerability to Change 2050 Regional Land Cover Vulnerability to Change 2050 Country What these layers model (and what they don’t model) The model focuses on human-based land cover changes and projects the extent of these changes to the year 2050. It seeks to find where agricultural and urban land cover will cover the planet in that year, and what areas are most vulnerable to change due to the expansion of the human footprint. It does not predict changes to other land cover types such as forests or other natural vegetation during that time period unless it is replaced by agriculture or urban land cover. It also doesn’t predict sea level rise unless the model detected a pattern in changes in bodies of water between 2010 and 2018. A few 300m pixels might have changed due to sea level rise during that timeframe, but not many. The model predicts land cover changes based upon patterns it found in the period 2010-2018. But it cannot predict future land use. This is partly because current land use is not necessarily a model input. In this model, land set aside as a result of political decisions, for example military bases or nature reserves, may be found to be filled in with urban or agricultural areas in 2050. This is because the model is blind to the political decisions that affect land use. Quantitative Variables used to create Models Biomass Crop Suitability Distance to Airports Distance to Cropland 2010 Distance to Primary Roads Distance to Railroads Distance to Secondary Roads Distance to Settled Areas Distance to Urban 2010 Elevation GDP Human Influence Index Population Density Precipitation Regions Slope Temperature Qualitative Variables used to create Models Biomes Ecoregions Irrigated Crops Protected Areas Continent Country Rainfed Crops Soil Classification Soil Depth Soil Drainage Soil pH Soil Texture在针对单一国家开展分析时，请使用此国家模型图层。该图层展示了截至2050年，全球各国土地覆盖受人类活动改造的相对脆弱性预测结果。本预测基于2010年与2018年的欧洲空间局气候变化倡议（ESA CCI）土地覆盖图制作完成。映射变量：截至2050年土地覆盖受人为活动影响的脆弱性。数据投影：圆柱等面积投影；拼接投影：圆柱等面积投影。空间范围：全球，像元尺寸：300米，数据类型：专题数据，可视比例尺：1:50000及更小比例尺。数据来源：克拉克大学（Clark University），发布日期：2021年4月，分析属性：分析优化型。 该图层的应用场景：可通过该图层开展分析，估算并对比2050年因人类活动扩张引发的全球土地覆盖变化脆弱性。该图层可用于生态规划，辅助优先划定保护区。 分析优化说明：若需使用该图层的分析优化特性，需由您所属的ArcGIS组织管理员启用该功能。有关启用该功能的详细说明，请参阅本文档的“区域数据托管”章节。分析优化特性意味着该图层不受分析尺寸限制，推荐与其他分析优化型图层配合开展多源分析。可访问ArcGIS生活地图集（ArcGIS Living Atlas）的“分析优化影像图层群组”页面，获取所有分析优化型影像图层的完整列表。 ArcGIS世界生活地图集中的6个克拉克大学2050年土地覆盖图层链接如下：土地覆盖与脆弱性模型共分为三个尺度：国家级、区域级与全球级。三者存在细微差异：国家级模型可针对特定区域的驱动因子进行精细化调优，而区域（大陆）级与全球级模型的权重在空间分布上更具一致性。 如何选择合适的图层？若您仅针对单个国家开展分析，或需要对邻近国家进行精准对比，请使用国家级图层。若需绘制大范围格局或分析地理跨度较大的多国区域，请根据研究区范围选择全球级或区域级图层。具体图层包括：2050年全球土地覆盖、2050年区域土地覆盖、2050年国家土地覆盖、2050年全球土地覆盖变化脆弱性、2050年区域土地覆盖变化脆弱性、2050年国家土地覆盖变化脆弱性。 图层模拟范围（及未模拟范围）：本模型聚焦于人类活动引发的土地覆盖变化，并将该变化趋势投影至2050年，旨在预测届时农业与城市用地的全球分布，以及受人类活动扩张影响最易发生变化的区域。除非被农业或城市用地取代，否则该模型不会预测森林或其他自然植被等其他土地覆盖类型的变化。此外，除非模型在2010-2018年间检测到水体变化模式，否则不会预测海平面上升。在该时间范围内，仅有少量300米像元可能因海平面上升发生变化，但占比极低。本模型基于2010-2018年间的变化模式预测土地覆盖变化，但无法预测未来土地利用情况，部分原因在于当前土地利用并未作为模型输入变量。在本模型中，因政治决策预留的土地（如军事基地或自然保护区）可能在2050年被城市或农业用地覆盖，这是因为模型无法识别影响土地利用的政治决策因素。 模型构建所用定量变量：生物量、作物适宜性、距机场距离、2010年距耕地距离、距一级公路距离、距铁路距离、距二级公路距离、距定居点距离、2010年距城市区域距离、海拔、国内生产总值（GDP）、人类影响指数、人口密度、降水分区、坡度、温度。 模型构建所用定性变量：生物群区、生态区、灌溉作物、保护区、大洲、国家、雨养作物、土壤分类、土壤深度、土壤排水性、土壤pH值、土壤质地。