Spatial associations between NDVI and environmental factors in the Heihe River Basin

Yuan, Liang; Chen, Xiaoqiang; Wang, Xiangyu; Xiong, Zhe; Song, Chunqiao

doi:10.1007/s11442-019-1676-0

Cited by 40 publications

(11 citation statements)

References 49 publications

(75 reference statements)

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“…The dynamic change of vegetation was generally at a high level in the Heihe River Basin between the 1980s and the 2010s. According to the change trends of vegetation in different elevation zones, the change rate of vegetation in the low and middle elevation zones was generally higher than that in the high-cold zone, which indicates that human activities could be considered a key role to vegetation change during the period from the 1980s to the 2010s because the range of human activities are mainly concentrated in the low and middle elevation zones, and it is difficult up to the high-cold zone [14,20,41].…”

Section: Discussionmentioning

confidence: 99%

“…The area of Ejina Banner in the lower reaches was deteriorate from an ecological barrier of the northwestern region to an important source of sandstorms [16], and the area of influence involves Northwest China, North China, and even East China [17,18]. In recent years, a large number of observations and statistical studies have been made in Heihe River Basin [19,20], especially in small watersheds or smaller scales [21]. However, the responses of spatial distribution in vegetation to climate change are mainly concentrated in some local areas and lack an analysis to the whole area of Heihe River Basin, especially in the different elevation zones [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Patterns of the Vertical Distribution of Vegetation in Heihe River Basin since the 1980s

Fan

2021

Forests

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The vertical distribution of vegetation in Heihe River Basin has presented a significant dynamic change in the different elevation zones since the 1980s. To explore the dynamic patterns of vegetation types located in the different elevation zones of Heihe River Basin, this study collected 440 field sampling datapoints of vegetation types, remote sensing images, climatic observation data, and DEM and preprocessed them. On the basis of the vegetation distribution and the terrain characteristics of Heihe River Basin, this study classified the vertical distribution of vegetation in Heihe River Basin into six vegetation zones, namely, the oasis farmland and desert zone, desert-steppe zone, dry scrub-steppe zone, mountain forest-steppe zone, subalpine scrub-meadow zone, and alpine cold desert-meadow zone. Moreover, the mean annual biotemperature (MAB) and total annual average precipitation (TAP) were used to analyze the relationship between vegetation change and climate change in the different elevation zones. The results show that the change rate of vegetation was up to 25.75% in Heihe River Basin. The area of vegetation that changed in the oasis farmland and desert zone was the largest (7224 km2), and the rate of vegetation that changed in the mountain forest-steppe zone was up to 56.93%. The mean annual biotemperature (MAB) and total annual average precipitation (TAP) in the six elevation zones showed an increasing trend, in which the increased rate of TAP presented a downward trend with the increase of elevation, and that of MAB showed a continuous upward trend with the increase of elevation. The change rate of vegetation was generally higher than that of MAB and TAP in the low and middle vegetation zones. The influence intensity of human activities on vegetation change in the lower and middle elevation zones of Heihe River Basin was greater than that in the high elevation zone between the 1980s and the 2010s. MAB is the major impact factor to vegetation change in the alpine cold zone of Heihe River Basin.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Patterns of the Vertical Distribution of Vegetation in Heihe River Basin since the 1980s

Fan

2021

Forests

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“…The maximum NDVI value was 0.76, which was located in the Zoigê wetland. By referring to related studies [36], the NDVI values were classified into 5 levels. The NDVI distribution was analysed in combination with the land-use types ( Figure 2c).…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal Variation of NDVI in the Vegetation Growing Season in the Source Region of the Yellow River, China

Wang

et al. 2020

IJGI

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Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area.

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“…NDVI is one of the best indicators to identify the growth status and spatial distribution density of vegetation (Yuan et al, 2019). There are linear correlations between NDVI and the spatial distribution density of plants.…”

Section: Spatial Patterns Of Lulc and Green Spacementioning

confidence: 99%

Monitoring thermal field, humidity field and energy balance over heterogeneous surfaces in the typical valley-city

Zhang

Mirzaei

et al. 2020

J. Geogr. Sci.

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Land use and land cover (LULC) alteration has changed original energy balance and heat fluxes between land and atmosphere, and thus affects the structure characteristics of temperature and humidity fields over urban heterogeneous surfaces in different spatio-temporal scales. Lanzhou is the most typical river valley city of China, it is chosen as the case study. Typical river valley terrain, rapid urbanization and severe air pollution have caused unique urban climate and urban heat island (UHI) effects in Lanzhou. Firstly, the spatial structure characteristics and dynamic evolution of temperature and humidity fields in autumn are simulated by mobile measurement experiment and GIS spatial analysis method. The results show that temperature and humidity fields have significant dynamic change within a day, and have multiple center and multiple intensity level characteristics. Then, LULC and normalized difference vegetation index (NDVI) are extracted from remote sensing images, the distribution patterns of temperature and humidity fields have close relationships with LULC and NDVI. Moreover, there is a significant positive correlation between impervious surface area and thermal field intensity. A positive correlation between NDVI value and humidity field intensity has been found as well as a negative correlation between NDVI value and thermal field intensity. Finally, heat fluxes and energy balance characteristics between ground and atmosphere are analyzed based on the Bowen-ratio System experiments. This study could provide theoretical support and practical guidance for urban planning, urban eco-environment construction and air pollution prevention of river valley city.

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Spatial associations between NDVI and environmental factors in the Heihe River Basin

Cited by 40 publications

References 49 publications

Dynamic Patterns of the Vertical Distribution of Vegetation in Heihe River Basin since the 1980s

Dynamic Patterns of the Vertical Distribution of Vegetation in Heihe River Basin since the 1980s

Spatiotemporal Variation of NDVI in the Vegetation Growing Season in the Source Region of the Yellow River, China

Monitoring thermal field, humidity field and energy balance over heterogeneous surfaces in the typical valley-city

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