The Impact of Land Cover Changes Surrounding Meteorological Stations on Measurements and Observations Using Landsat Satellite Data

Meteorological station metadata are essential for assessing the homogeneity of climatic measurement and observation time series. Among these metadata, land cover characteristics in the vicinity of the station are particularly important. Changes in land cover around a meteorological station can influence measurement outcomes, thereby compromising the homogeneity of climatic data.
Additionally, the geographical location of meteorological stations may be moved. Depending on the distance of relocation, the structure and composition of land cover surrounding the station can vary significantly. Substantial changes in the proportions of land cover classes near a meteorological station may considerably affect the recorded measurements and observations, further disrupting data homogeneity.
This study employed two satellite-derived land cover datasets with a spatial resolution of 30 meters, both based on Landsat imagery: GLanCE (NASA, 2001–2019) and GLC_FCS30D (AIRI CAS, 1985–2022). Changes in land cover structure were analyzed for 62 synoptic meteorological stations in Poland from 1985 to 2022 at both local (1 km and 2 km) and mesoscale (10 km and 30 km) radii. The analysis of land cover changes was also performed for the main wind directional sectors. The analysis distinguished stations that remained stationary from those that changed geographical location one or more times. For two selected synoptic meteorological stations—one stationary and one relocated—an assessment was conducted to determine the potential influence of land cover changes on recorded meteorological variables, using homogeneity tests and machine learning techniques to detect anomalies.

Keywords: meteorological station metadata, land cover changes, data homogeneity, climatic time series

References:
Friedl, M. A., Woodcock, C. E., Olofsson, P., Zhu, Z., Loveland, T., Stanimirova, R., Arevalo, P., Bullock, E., Hu, K.-T., Zhang, Y., Turlej, K., Tarrio, K., McAvoy, K., Gorelick, N., Wang, J. A., Barber, C. P., & Souza, C. (2022). Medium Spatial Resolution Mapping of Global Land Cover and Land Cover Change Across Multiple Decades From Landsat. Frontiers in Remote Sensing, 3. https://www.frontiersin.org/articles/10.3389/frsen.2022.894571
Zhang, X., Zhao, T., Xu, H., Liu, W., Wang, J., Chen, X., and Liu, L. (2024). GLC_FCS30D: the first global 30-m land-cover dynamic monitoring product with a fine classification system from 1985 to 2022 using dense time-series Landsat imagery and continuous change-detection method, Earth Syst. Sci. Data, 16, 1353–1381. https://doi.org/10.5194/essd-16-1353-2024