Data from: A general-purpose spatial survey design for collaborative science and monitoring of global environmental change: the global grid

Recent guidance on environmental modeling and global land-cover validation stresses the need for a probability-based design. Additionally, spatial balance has also been recommended as it ensures more efficient sampling, which is particularly relevant for understanding land use change. In this paper I describe a global sample design and database called the Global Grid (GG) that has both of these statistical characteristics, as well as being flexible, multi-scale, and globally comprehensive. The GG is intended to facilitate collaborative science and monitoring of land changes among local, regional, and national groups of scientists and citizens, and it is provided in a variety of open source formats to promote collaborative and citizen science. Since the GG sample grid is provided at multiple scales and is globally comprehensive, it provides a universal, readily-available sample. It also supports uneven probability sample designs through filtering sample locations by user-defined strata. The GG is not appropriate for use at locations above ±85° because the shape and topological distortion of quadrants becomes extreme near the poles. Additionally, the file sizes of the GG datasets are very large at fine scale (resolution ~600 m × 600 m) and require a 64-bit integer representation.当前环境建模与全球土地覆盖验证领域的权威指南均强调，需采用基于概率的采样设计方案。同时，指南还推荐使用空间平衡采样策略，因其可提升采样效率，这对于解析土地利用变化规律尤为关键。本文介绍了一款名为全球网格（Global Grid，GG）的全球采样设计与数据库，其兼具上述两类核心统计特性，同时具备灵活性、多尺度性与全球覆盖性。该数据库旨在助力本地、区域及国家级的科研人员与公民群体开展土地变化协同科研与监测工作，并以多种开源格式发布，以推动协同科研与公民科学的发展。由于GG采样网格支持多尺度发布且实现全球覆盖，因此可提供通用且易于获取的采样资源。此外，其支持通过用户自定义分层对采样点位进行筛选，从而实现不等概率采样设计。GG不适用于南北纬85°以上的区域，因为在极地附近，网格象限的形状与拓扑畸变会变得极为严重。此外，GG数据集在精细尺度（分辨率约600米×600米）下文件体量极大，且需采用64位整数进行存储表示。