Culler M, Wickham J, Nash M, Clement M T
Oak Ridge Institute for Science and Education (ORISE) Participant, U.S. EPA, Center for Public Health and Environmental Assessment, Office of Research and Development, 109 T.W. Alexander Dr., Research Triangle Park, NC 27711.
U.S. EPA, Center for Public Health and Environmental Assessment, Office of Research and Development, 109 T.W. Alexander Dr., Research Triangle Park, NC 27711.
Remote Sens Appl. 2024 Aug;35. doi: 10.1016/j.rsase.2024.101247.
Pattern-focused environmental equity research has been underpinned by high-resolution remotely sensed data to uncover spatial relationships between environmental amenities (e.g., urban tree cover) and socio-economic status (SES). A constraint imposed by reliance on high-resolution data is the inability to examine temporal patterns, primarily because of the cost of data production and the nascent state of high-resolution land cover mapping. The lack of temporal monitoring is a clear gap in pattern-focused environmental equity research. We examined temporal (2001 - 2019) relationships between a disamenity, impervious cover (IC), and demographic attributes for the entirety of the conterminous United States. Our main finding was 2001 - 2019 increases in IC were more pervasive in minority communities but these communities were not necessarily poor, and only rarely poorly educated or non-English speaking. We supported our use of IC from moderate resolution data by comparing it to high-resolution data for 24 cities within the conterminous United States. Mean Absolute Deviation (MAD) was 4.8% overall, ranging from 2.2% to 11.3% across the 24 locations. Differences in classification objectives contributed to differences in %IC estimates between the two sources.
以模式为重点的环境公平研究一直以高分辨率遥感数据为支撑，以揭示环境便利设施（如城市树木覆盖）与社会经济地位（SES）之间的空间关系。依赖高分辨率数据带来的一个限制是无法研究时间模式，主要原因是数据生产成本以及高分辨率土地覆盖制图尚处于起步阶段。缺乏时间监测是聚焦模式的环境公平研究中一个明显的空白。我们研究了美国本土全境一种不利因素——不透水表面（IC）与人口属性之间的时间关系（2001年至2019年）。我们的主要发现是，2001年至2019年期间，IC的增加在少数族裔社区更为普遍，但这些社区不一定贫穷，而且很少是受教育程度低或说非英语的社区。我们通过将美国本土24个城市的中等分辨率数据中的IC与高分辨率数据进行比较，来支持我们对中等分辨率数据中IC的使用。总体平均绝对偏差（MAD）为4.8%，24个地点的范围在2.2%至11.3%之间。分类目标的差异导致了两种数据源之间IC估计百分比的差异。
