USA Annual NLCD - Land Cover Confidence

Beta Notice: This item is currently in beta and is intended for early access, testing, and feedback. It is not recommended for production use, as functionality and content are subject to change without notice. In some areas a pixel's land cover class is more difficult to determine than in other areas. This annual time-enabled service of the National Land Cover Database gives a percent confidence that each pixel in the NLCD is the class the annual NLCD layer says it is. Use this layer with the USA Annual - Land Cover layer. The Annual NLCD layers are produced using supervised classification with a series of deep learning models. Part of the output of these models is a probability value for a pixel's output land cover class. Keep in mind that probability values are an expression of confidence. Values are not calibrated and should not be understood as an absolute likelihood that the land cover class given is correct. Additional information about these annual NLCD layers may be found in the USGS Science Product User Guide. Dataset Summary Phenomenon Mapped: Percent confidence accompanying each pixel's NLCD land cover class. Geographic Extent: Contiguous USA (lower 48 states + DC) Mosaic Projection: Albers Equal Area Conic, on WGS84 spheroid (AEA_WGS84) Data Coordinate System: Albers Equal Area Conic, on WGS84 spheroid (AEA_WGS84) Cell Size: 30 meters Pixel Depth: 8 Bit Unsigned Source Type: Thematic Time Extent: Annually 1985-2024 Analysis: Analysis-Optimized Update Frequency: Annually Source: National Land Cover Database, Multi-Resolution Land Characteristics Consortium Data Vintage: Version 1.1, June 25, 2025 Publication Date: 2025 What can you do with this layer? Reduce influence of less certain land cover types in models. Apply transparency to land cover to make it less strong where a land cover status is less certain. Identify the certainty of a particular pixel's land cover status. Read the Explore 40 Years of Analysis-Ready Annual NLCD Landcover blog. 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 Processing Templates Blue to Ochre Percent Confidence Renderer - A stretched ramp converted to a color ramp which shows less confident places in grays and light oranges and the most confident places in deep blue. Grayscale Percent Confidence Renderer - Displays more confident places in light gray and less confident places in dark gray. There are a few pixels that are greater than 100 percent confidence due to extrapolation and these appear in dark gray also. Values 0-100 Only Grayscale Renderer - Displays more confident places in light gray and less confident places in dark gray. There are a few pixels that are greater than 100 percent confidence due to extrapolation and in this renderer those values are converted to nodata. Questions? Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.测试版声明：本数据集目前处于测试阶段，仅面向早期访问、测试及反馈用途，不建议用于生产环境，因其功能与内容可能未经通知即发生变更。 部分区域的像元土地覆盖类别判定难度高于其他区域。本美国国家土地覆盖数据库（National Land Cover Database，NLCD）的年度时序服务，可提供NLCD中每个像元对应年度NLCD图层所标注类别的置信百分比。请结合「美国年度土地覆盖」图层使用本数据层。 年度NLCD图层通过一系列深度学习模型的监督分类生成，这类模型的输出之一为像元对应土地覆盖类别的概率值。需注意，概率值仅为置信度的表达形式，未经过校准，不应将其视为对应土地覆盖类别正确的绝对可能性。更多关于年度NLCD图层的信息可参阅美国地质调查局（USGS）科学产品用户指南。 数据集摘要 映射现象：每个像元对应的NLCD土地覆盖类别置信百分比 地理覆盖范围：美国本土（48个毗邻州+哥伦比亚特区） 镶嵌投影：基于WGS84椭球体的阿尔伯斯等面积圆锥投影（Albers Equal Area Conic，AEA_WGS84） 数据坐标系：基于WGS84椭球体的阿尔伯斯等面积圆锥投影（AEA_WGS84） 像元尺寸：30米 像元深度：8位无符号整型 源数据类型：专题数据 时间范围：1985-2024年年度数据 分析优化：已针对分析优化 更新频率：年度更新 数据来源：美国国家土地覆盖数据库（National Land Cover Database，NLCD）、多分辨率土地特征联盟（Multi-Resolution Land Characteristics Consortium） 数据版本：2025年6月25日发布的1.1版 发布日期：2025年 本数据层的应用场景 1. 降低模型中不确定性较高的土地覆盖类型的影响 2. 为土地覆盖图层添加透明度，在土地覆盖状态确定性较低的区域降低图层显示强度 3. 识别单个像元土地覆盖状态的确定性 可参阅《探索40年分析就绪型年度NLCD土地覆盖》博客文章。 分析说明 若要使用本数据层的分析优化功能，需由您所在的ArcGIS组织管理员启用该功能。有关启用此功能的更多信息，请参阅本文档「区域数据托管」章节。分析优化意味着该数据层无分析尺寸限制，推荐用于与其他分析优化型数据层的多源分析。如需完整的分析优化型影像图层列表，请参阅ArcGIS Living Atlas：分析优化型影像图层群组。 处理模板 1. 蓝至赭石色置信度渲染器：采用拉伸渐变转换为色彩渐变，其中确定性较低的区域以灰色和浅橙色显示，确定性最高的区域以深蓝色显示。 2. 灰度置信度渲染器：确定性较高的区域以浅灰色显示，确定性较低的区域以深灰色显示。由于外推计算，存在少量置信度超过100%的像元，此类像元在该渲染器中同样以深灰色显示。 3. 仅0-100值灰度渲染器：确定性较高的区域以浅灰色显示，确定性较低的区域以深灰色显示。由于外推计算产生的超100%置信度像元将被转换为无数据值。 如有疑问？请在下方留言，我们将尽快回复您。