Monitoring land surface thermal environments under the background of landscape patterns in arid regions: A case study in Aksu river basin

Zhuang, Qingwei; Wu, Shanshan; Yan, Yuyan; Niu, Yaxuan; Yang, Fan; Xie, Chengke

doi:10.1016/j.scitotenv.2019.136336

Cited by 21 publications

(10 citation statements)

References 90 publications

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“…The introduction of new technologies should allow for the rapid recovery of a forest [20] that can bind carbon from the atmosphere [19,20], produce wood that can serve as a biofuel [21], and retain more water in the landscape, thereby cooling the atmosphere. The secondary impact of rapid forest recovery is the long-term stabilization of annual logging [22][23][24] and hence also the stabilization of wood prices [25][26][27][28], including the sustainability of the whole foresty sector [29][30][31][32][33][34].…”

Section: Discussionmentioning

confidence: 99%

The Impacts of Calamity Logging on the Development of Spruce Wood Prices in Czech Forestry

Toth

Maitah

Malec

et al. 2020

Forests

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Currently, the decline in spruce wood prices is a serious problem for the forestry sector in the Czech Republic. We estimate that the fall in wood prices in European markets causes losses not only to the forestry companies producing, harvesting, and processing the wood, but also to the workers in the sector. These losses are mainly caused by a combination of several natural factors: drought, climate change, and the effects of bark beetles. In particular, spruce bark beetles cause the greatest damage. Due to this bark beetle calamity, unplanned logging has increased. In 2019, these damages have culminated. Almost 100 million m3 of wood has been harvested over the last decade due to the bark beetle and more than half of this volume has been mined in the last four years. Therefore, the losses in the forestry sector are around EUR 1.12 billion. The aim of this study is an analysis of the relationship between the volume of incidental logging and the decline in the price of spruce wood. These results show the strong correlation between the measure of unplanned wood harvesting and the decrease in wood prices, as well as an estimate of price development if the upward trend of incidental mining continues. The average price of wood in the Czech Republic could thus reach a historical minimum of EUR 79.39 per m3 of spruce and category SM/JE II (spruce/fir). In addition, the decline in wood prices will be reflected in the management of forestry and timber businesses, including stagnant wages for forestry workers. The socio-economic impact of the bark beetle calamity is high and is most affected by the decline in spruce timber prices.

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Section: Discussionmentioning

confidence: 99%

The Impacts of Calamity Logging on the Development of Spruce Wood Prices in Czech Forestry

Toth

Maitah

Malec

et al. 2020

Forests

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“…Gao is with the Key Laboratory of Quantitative Remote Sensing Information Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China (email: gaocaixia@aoe.ac.cn) interface between the land surface and the atmosphere [1,2]. It has been applied in a variety of studies, e.g., drought monitoring [3,4], thermal environment monitoring [5][6][7], and global climate change [8][9][10][11]. LST is identified as a key Earth Science Data Record (ESDR) by the National Aeronautics and Space Administration (NASA) and as one of the ten Essential Climate Variables (ECVs) in the land biosphere by the Global Climate Observing System (GCOS) [12].…”

mentioning

confidence: 99%

Spatio-Temporal Distribution Characteristics of Global Annual Maximum Land Surface Temperature Derived from MODIS Thermal Infrared Data From 2003 to 2019

Duan

Huang

Liu

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Land surface temperature (LST) is an important parameter in the physical processes of energy and water balance at the local and global scales. Annual maximum composite of LST provides important information about ecosystem exposure patterns to extreme LST. It has the ability to characterize the changes associated with extreme climatic events and significant land-cover changes. In this study, the spatio-temporal distribution characteristics of global annual maximum LST extracted from the MODIS LST product (MYD11A1) during the period 2003-2019 were investigated. The results indicate that the spatial pattern of annual maximum LST is associated with the biophysical and biogeographic factors of Earth's ecosystems. The inter-annual variability of annual maximum LST during the period 2003-2019 is relatively small. The change trend of annual maximum LST during the period 2003-2019 in the globe is 0.1 °C/decade. The annual maximum LST data was applied to detect thermal anomalies, including drought, heat wave, and ice melting. Some significant thermal anomaly events were well identified using the annual maximum LST data with standardized anomaly index larger than 2.5.

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“…[ 61 ]. The arid and semi-arid areas form a unique landscape unit, which is caused by the difference between the “furnace” desert and the underlying surface of other landscape types and the uneven distribution of surface heat [ 62 ]. Compared with the urban agglomeration along the Yellow River in Ningxia and the urban agglomeration in Hubao-Eyu, which are also located in arid and semi-arid regions, the urban agglomeration on the northern slopes of the Tianshan Mountains has the highest drought level.…”

Section: Discussionmentioning

confidence: 99%

“…The influence of landscape patterns on LST is unstable, and multiple scenarios need to be considered when exploring the correlation between landscape elements and LST. Areas with high connectivity of bare soil patches have higher LST, and regions with high connectivity of green land patches have lower LST, with regional distribution characteristics; but, as a whole, AI and AREA_MN are negatively correlated with LST, and PD is positively correlated with LST [ 62 ]. Therefore, in order to maintain the sustainable development of oasis ecosystems, attention needs to be paid to the construction of green and blue landscapes, which are essential for oasis ecological restoration, biodiversity, and the suitability of the human living environment.…”

Section: Discussionmentioning

confidence: 99%

Spatial and Temporal Variation of Land Surface Temperature and Its Spatially Heterogeneous Response in the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains, Northwest China

Zhang

Kasimu

Liang

et al. 2022

IJERPH

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An in-depth study of the influence mechanism of oasis land surface temperature (LST) in arid regions is essential to promote the stable development of the ecological environment in dry areas. Based on MODIS, MYD11A2 long time series data from 2003 to 2020, the Mann–Kendall nonparametric test, the Sen slope, combined with the Hurst index, were used to analyze and predict the trend of LST changes in the urban agglomeration on the northern slopes of the Tianshan Mountains. This paper selected nine influencing factors of the slope, aspect, air temperature, normalized vegetation index (NDVI), precipitation (P), nighttime light index (NTL), patch density (PD), mean patch area (AREA_MN), and aggregation index (AI) to analyze the spatial heterogeneity of LST from global and local perspectives using the geodetector (GD) model and multi-scale geo-weighted regression (MGWR) model. The results showed that the average LSTs of the urban agglomeration on the northern slopes of the Tianshan Mountains in spring, summer, autumn, and winter were 31.53 °C, 47.29 °C, 22.38 °C, and −5.20 °C in the four seasons from 2003 to 2020, respectively. Except for autumn, the LST of all seasons showed an increasing trend, bare soil and grass land had a warming effect, and agricultural land had a cooling effect. The results of factor detection showed that air temperature, P, and NDVI were the dominant factors affecting the spatial variation of LST. The interaction detection results showed that the interaction between air temperature and NDVI was the most significant, and the two-factor interaction was more effective than the single-factor effect on LST. The MGWR model results showed that the effects of PD on LST were positively correlated, and the impact of AREA_MN and AI on LST were negatively correlated, indicating that the dense landscape of patches has a cooling effect on LST. Overall, this study provides information for managers to carry out more targeted ecological stability regulations in arid zone oases and facilitates the development of regulatory measures to maintain the cold island effect and improve the environment.

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Monitoring land surface thermal environments under the background of landscape patterns in arid regions: A case study in Aksu river basin

Cited by 21 publications

References 90 publications

The Impacts of Calamity Logging on the Development of Spruce Wood Prices in Czech Forestry

The Impacts of Calamity Logging on the Development of Spruce Wood Prices in Czech Forestry

Spatio-Temporal Distribution Characteristics of Global Annual Maximum Land Surface Temperature Derived from MODIS Thermal Infrared Data From 2003 to 2019

Spatial and Temporal Variation of Land Surface Temperature and Its Spatially Heterogeneous Response in the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains, Northwest China

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