Analysis of land surface temperature variation based on MODIS data a case study of the agricultural pastural ecotone of northern China

Wei, Baocheng; Bao, Yuhai; Yu, Shen; Yin, Shuiqing

doi:10.1016/j.jag.2021.102342

Cited by 23 publications

(18 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The average value was 0.08 °C /Y, and it showed an increasing trend on the whole. The rising rate was higher than that in northern China [13]. About 99.04% of the region exhibited an increasing trend (Slope > 0), with 0.99% and 24.88% of…”

Section: Trend Variation Characteristics Of Lstmentioning

confidence: 73%

“…The slope analysis method was used in this study to investigate the variation trend of LST in the province [13,16]. The slope expression is as follows:…”

Section: Spatiotemporal Variation Of Lstmentioning

confidence: 99%

“…Compared with the traditional station-based NSAT or SAT, satellite-derived LST is a unique dataset with advantage of spatial continuity [11,12]. In addition, LST can be used as an important tracer of the change of surface characteristics because LST is more sensitive to changes of energy balance and surficial properties than that of NSAT and SAT [13,14]. Therefore, more attention should be paid to spatiotemporal variation of LST.…”

Section: Introductionmentioning

confidence: 99%

“…Moderate Resolution Imaging Spectroradiometer (MODIS) is regarded as the most popular sensor for retrieving LST due to its free available and high observation frequency [13]. With the time extension of the available MODIS LST product, there have been more and more studies produced on the spatiotemporal variation of time-series LST for different regions.…”

Section: Introductionmentioning

confidence: 99%

“…Yu et al (2020) presented the inter-annual spatiotemporal variation of LST for China from 2003 to 2017 [14]. Wei et al (2021) analyzed the LST variation in the agricultural pastoral ecotone of northern China from 2003 to 2020 [13]. Xing et al (2020) examined the year-to-year variations of LST under clear-sky conditions for the whole world based on annual temperature cycle (ATC) model [17].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Spatiotemporal Variation of Land Surface Temperature in Henan Province of China from 2003 to 2021

Qin

Zhao

et al. 2022

Land

View full text Add to dashboard Cite

Land surface temperature (LST) is a key parameter closely related to various land surface processes and surface-atmosphere interactions. Analysis of spatiotemporal variation of time-series LST may provide useful information to understand eco-climatic characteristics. In this study, the spatiotemporal pattern of LST and its trend characteristics in Henan Province were examined based on MODIS LST products from 2003 to 2021. In addition, the influences of land cover types, Nighttime Light data (NTL) and Normalized Difference Moisture Index (NDMI) on LST variation were analyzed. The results indicated that: (i) The LST showed slight and rapid decreasing trend for 2004–2010 and 2018–2020, respectively, whereas an obvious increasing and slight increasing trend occurred for 2010–2013 and 2014–2018. In terms of spatial pattern, high-temperature, and sub-high-temperature were mainly distributed in the central part of the province with higher level of industrialization and urbanization at the annual, spring, summer, and daytime scales. While in fall, winter, and the nighttime, the spatial distribution of LST exhibited decreased trend from the southern part to the northern part of the province, the largest Standard Deviation (STD) was observed in summer. (ii) The interannual variation rate of LST was 0.08 °C/Y. The increasing trend mainly occurred in urban and built-up areas. At the seasonal scales, the rising rate decreased sequentially in the order of fall, winter, spring, and summer. In addition, the rising rate in the daytime was higher than that in the nighttime. (iii) LST increased along with the expansion of urban and built-up lands, except in winter. At the annual scales, 84.69% of areas with NTL data exhibited a positive correlation with LST, and NDMI in the western part with high elevation presented a significantly positive correlation to LST, while a significantly negative correlation occurred in urban and built-up areas. The cooling effect of NDMI on LST in the daytime was greater than that in the nighttime. In cropland areas, LST showed a non-significant correlation with NDMI at the annual scale, and a significantly negative correlation with NDMI in spring, summer, and fall. The influence mechanism of cropland on the variation of LST at different timescales needs to be further explored. These findings might provide some hints to understand climate change and its causes in the province.

show abstract

Section: Trend Variation Characteristics Of Lstmentioning

confidence: 73%

“…The slope analysis method was used in this study to investigate the variation trend of LST in the province [13,16]. The slope expression is as follows:…”

Section: Spatiotemporal Variation Of Lstmentioning

confidence: 99%