Spatial Scale Effects of the Relationship between Fractional Vegetation Coverage and Land Surface Temperature in Horqin Sandy Land, North China

Abstract

Sandy range land refers to a major component of grassland area types in the semi-arid area of northern China. Monitoring of vegetation and land surface temperature (LST) using remote sensing technology can help determine the degree of desertification in a regional and/or sub regional scale, as in the Horqin Sandy Land selected in this study. Correlation analysis was performed to examine the relationship between the fractional vegetation coverage (FVC) and the LST within one growing season (from May to August 2017), at different spatial scales. The results showed that the FVC increased from 0.12 in May to 0.29 in August, and the LST increased first and then declined. The highest LST was 41.68 °C in July, while the lowest was 28.62 °C in August. At the grid scale, the LST increased first and then declined with the increase of the FVC on 25 May, 10 June, and 29 August; the FVC ranged from 0.29–0.38, 0.27–0.32, and 0.29–0.38 with the preference of the ‘turning point’, respectively. A negative correlation was identified between the FVC and the LST and without any ‘turning point’ in the fitting curve on 28 July. The correlation between FVC and LST complied with the grid scale at the sample area scale. The coupling analysis of landscape pattern expressed by FVC and LST showed that, the landscape evenness, Euclidean nearest neighbor distance, and landscape splitting degree all showed strong coupling correlation in any study period (P). The landscape aggregation of FVC and LST showed a good coupling at the relatively high and low air temperature conditions of P1 and P3. Landscape contagion showed a good coupling between FVC and LST at relatively moderate air temperature condition of P1 and P4. Air temperature conditions and characteristics of vegetation coverage should be considered for a more targeted analysis when analyzing the relationship between FVC and LST and attention should be paid to the timing and type of study area in practical application.

Eco-environmental quality assessment of the artificial oasis of Ningxia section of the Yellow River with the MRSEI approach

“…Importance values indicated that urban and built-up lands and barren land area with low ecological quality in 2000 shown to have a greater impact on MRSEI, while water body and wetland with higher ecological quality in 2020 had a greater impact on MRSEI, this result is basically consistent with that of RSEI change research in Dongting Lake and can be mutually verified (Yuan et al, 2021). However, a common defect of RSEI and MRSEI is that the participating evaluation factors LDI, NDVI, and NDBSI reflect the long-term accumulated surface reflection characteristics, while Wet and LST only reflect the short-term surface reflection characteristics (Bindlish and Barros, 2001;Sobrino et al, 2008;Qiao et al, 2021). The removal of this uncertainty due to time scale mismatch is a challenge for RSEI and MRSEI applications.…”

“…Especially in the pattern analysis of land surface temperature (LST), it was found that the heat island effect in Leipzig (Germany), was more reliable in densely urbanized areas than in areas with low population density (Schwarz et al, 2012). The sandy vegetation pattern in Horqin (China) was negatively correlated with land surface temperature, and the more complex the vegetation structure, the closer the correlation (Qiao et al, 2021). These studies are of great significance for carrying out more targeted ecological restoration work, and are also the current hotspots for quantitatively describing and estimating the spatiotemporal dynamics of eco-environmental quality and promoting sustainable development in different regions.…”

Pd-Catalyzed C(sp3)–H Biarylation via Transient Directing Group Strategy

“…To improve the yield of this reaction, a screening of different ligands (TDG1−TDG5) was then carried out (Table 1, entries 1−5). It was found that the reaction with tert-leucine (TDG4) as the directing group gave a better yield (Table 1, entry 4); further screening of the solvents (Table 1, entries 6− 8) showed that the mixed solvent system HFIP/AcOH (9/1) proved to be more effective leading to a 42% yield of 3a (Table 1, entry 7). Next, the yield was increased to 49% by increasing the amount of transient directing ligand (TDG4) to 40 mol % (Table 1, entry 9).…”

“…2 The remarkable progress has been applied in C(sp 2 )−H functionalization of aromatic aldehydes and ketones by employing monodentate or bidentate transient directing groups, such as arylation, 3 halogenation, 3d,4 hydroxylation, 5 methoxylation, 4b alkylation, 4a,6 amidation, 7 and selenylation. 8 Meanwhile, more challenging C(sp 3 )−H bond functionalizations of aliphatic aldehydes and ketones with various transient ligands have been significantly developed by the groups of Yu, 9 Ge, 10 Bull, 11 Wei, 12 Zhou, 13 Zhang, 14 and Li. 15 Unsurprisingly, the benzylic C(sp 3 )−H functionalization of 2-alkylbenzaldehyde, a critical building block, 16 has been accomplished with this novel synthetic strategy.…”

Evaluation of Spatial Fairness of Urban Public Transport Service：a Case Study of Wuhan City

“…Many scholars at home and abroad have done a lot of research in the field of public transportation. Evaluated the * Corresponding author accessibility and fairness of public transport and car transport from the perspective of time cost of traffic travel (Xi ,2020).Evaluated the scale effect and spatial effect affecting the spatial fairness mechanism of public transport (Li ,2019) .Studied the influence of spatial scale changes on bus fairness evaluation (Qiao, 2021), bus system optimization (Bai, 2017) and (Ge, 2006) and (Wirasinghe, 1981) and (Li, Bertini, 2009), and public transport accessibility (Ribeiro, 2021) and (Gao, Zhang,2022) and (Liu, Wang, 2011). Public transport passenger flow analysis (Gutié rrez et al, 2020) and (Liang, 2007), multi-use space autocorrelation analysis (Zhang et al, 2012), Gini coefficient (Liu et al, 2021), kernel density analysis (Yu, Ai, 2012) and other research methods in relevant literature.…”