Combining flux tower measurements with remote sensing or land surface models is generally regarded as an efficient method to scale up flux data from site to region. However, due to the heterogeneous nature of the vegetated land surface, the changing flux source areas and the mismatching between ground source areas and remote sensing grids, direct use of in-situ flux measurements can lead to major scaling bias if their spatial representativeness is unknown. Here, we calculate and assess the spatial representativeness of 15 flux sites across northern China in two aspects: first, examine how well a tower represents fluxes from the specific targeted vegetation type, which is called vegetation-type level; and, second, examine how representative is the flux tower footprint of the broader landscape or regional extents, which is called spatial-scale level. We select fraction of target vegetation type (FTVT) and Normalized Difference Vegetation Index (NDVI) as key indicators to calculate the spatial representativeness of 15 EC sites. Then, these sites were ranked into four grades based on FTVT or cluster analysis from high to low in order: (1) homogeneous; (2) representative; (3) acceptable; and (4) disturbed measurements. The results indicate that: (1) Footprint climatology for each site was mainly distributed in an irregular shape, had similar spatial pattern as spatial distribution of prevailing wind direction; (2) At vegetation-type level, the number of homogeneous, representative, acceptable and disturbed measurements is 8, 4, 1 and 2, respectively. The average FTVT was 0.83, grass and crop sites had greater representativeness than forest sites; (3) At spatial-scale level, flux sites with zonal vegetation had greater representativeness than non-zonal vegetation sites, and the scales were further divided into three sub-scales: (a) in flux site scale, the average of absolute NDVI bias was 4.34%, the number of the above four grades is 9, 4, 1 and 1, respectively; (b) in remote sensing pixel scale, the average of absolute NDVI bias was 8.27%, the number is 7, 2, 2 and 4, respectively; (c) in land model grid scale, the average of absolute NDVI bias was 12.13%, the number is 5, 4, 3 and 3. These results demonstrate the variation of spatial representativeness of flux measurements among different application levels and scales and highlighted the importance of proper interpretation of EC flux measurements. These results also suggest that source area of EC flux should be involved in model validation and/or calibration with EC flux measurements.

Abandoned mines are typical areas of soil erosion. Landscape transformation of abandoned mines is an important means to balance the dual objectives of regional ecological restoration and industrial heritage protection, but the secondary development and construction process of mining relics require long-term monitoring with objective scientific indicators and effective assessment of their management effectiveness. This paper takes Tongluo Mountain Mining Park in Chongqing as an example and uses a remote sensing ecological index (RSEI) based on Landsat-8 image data to assess the spatial and temporal differences in the dynamic changes in the ecological and environmental quality of tertiary relic reserves with different degrees of development and protection in the park. Results showed that: ① The effect of vegetation cover, which can significantly improve soil and water conservation capacity. ② The RSEI is applicable to the evaluation of the effectiveness of ecological management of mines with a large amount of bare soil areas. ③ The mean value of the RSEI in the region as a whole increased by 0.090, and the mean values of the RSEI in the primary, secondary and tertiary relic reserves increased by 0.121, 0.112 and 0.006, respectively. ④ The increase in the RSEI in the study area is mainly related to the significant decrease in the dryness index (NDBSI) and the increase in the humidity index (WET). The remote sensing ecological index can objectively reflect the difference in the spatial and temporal dynamics of the ecological environment in tertiary relic protection, and this study provides a theoretical reference for the ecological assessment of secondary development-based management under difficult site conditions.

In order to meet the requirements for comprehensive and multidimensional generalization of ecological management effectiveness evaluation indexes in the context of ecological restoration advocating comprehensive management by multiple means, this paper explores the rationality of using RSEI as an ecological management effectiveness evaluation index to adapt to the systematic transformation of the management goal of abandoned mine restoration from ecological restoration to regional socioeconomic sustainable development. Based on Landsat-8 image data, the remote sensing ecological index (RSEI) was used to evaluate the dynamic changes and spatial and temporal differences of the ecological environment in the study area under the long-term multimeans comprehensive management. The RSEI is suitable for evaluating the effectiveness of comprehensive ecological management in mining areas with a large amount of bare soil. The regional RSEI mean value increased by 0.029 in the early stage and 0.051 in the later stage by fragmentation management, indicating a better effect of multimeans comprehensive management. The remote sensing ecological index can objectively reflect the difference of spatial distribution characteristics of ecological environment in the four “Ecological+” governance regions. It can both objectively reflect the ecological status of the study area and reflect the differentiated spatial distribution characteristics of the ecological environment in different treatment areas, which is of long-term practical significance to the ecological construction of the study area. This study provides a theoretical reference for ecological assessment of complex situation under difficult site conditions.