Driving factor analysis on the vegetation changes derived from the Landsat TM images in Beijing

Baoquan, 贾宝全 Jia; Rusong, 王如松 Wang; 贾宝全,

doi:10.5846/stxb201208251199

Cited by 7 publications

(5 citation statements)

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“…At present, as a steady source of water, recycled water plays an important role in alleviating water scarcity in urban areas and restoring wetland functions [2]. However, the chemical characteristics of recycled water might cause many adverse e ects to restrict the application of recycled water wetlands [3][4][5]. With the increasing use of recycled water in urban wetlands, monitoring the status of plant growth and eutrophication in large constructed wetlands is of great signi cance for wetland management [6].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, some previous work suggested that there is a certain relationship between the nitrogen content in wetland plants and the nitrogen concentration in water [23,24], which implied that the spectral reflectance characteristics of wetland plants can be used to indirectly estimate the nitrogen concentration in water. In this study, to further explore the relationship between spectral characteristics of the wetland plant canopy and environmental TN content (TN content in water and TN content in plants): (1) We collected the reflectance spectra of the plant canopy and measured the total nitrogen (TN) content in water and plants in Beijing Bai River wetland; (2) Several multiple regression models were employed to estimate TN contents in plants (Phragmites australis and Typha angustifolia) and TN contents in water from the spectral reflectance data; (3) is study is expected to provide scientific evidence for the potential application of remote sensing to monitor nitrogen in wetland and to provide the strategic thinking for wetland restoration and reuse of recycled water in urban wetlands.…”

Section: Introductionmentioning

confidence: 99%

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Nitrogen Inversion Model in a Wetland Environment Based on the Canopy Reflectance of Emergent Plants

Zhao

Zhu

et al. 2022

Advances in Meteorology

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Reuse of reclaimed water in constructed wetlands is a promising way to conserve water resources and improve water quality, and it is playing a very important role in wetland restoration and reconstruction. This study utilized reflectance spectra of wetland vegetation to estimate nitrogen content in water in the Beijing Bai River constructed wetland, a typically constructed wetland that uses reclaimed water. Canopy reflectance spectra of two dominant plants in the wetland, including reed and cattail, were acquired using a spectrometer (350–2500 nm). Simultaneously, water samples were collected to measure water quality. To establish the appreciate relationship between total nitrogen content (TN) and reflectance spectra, both simple and multiple regression models, including simple ration spectral index (SR), normalized difference spectral index (ND), stepwise multiple linear regression (SMLR) model, and partial least squares regression (PLSR), were adopted in this study. The results showed that (1) compared with simple regression models (SR and ND), multiple regressions models (SMLR and PLSR) could provide a more accurate estimation of TN concentration in the wetland environment. Among these models, the PLSR model had the highest accuracy and was proven to be the most useful tool to reveal the relationship between the spectral reflectance of wetland plants and the total nitrogen consistency of wetland at the canopy scale. (2) The inversion effect of TN concentration in water is slightly better than that of wetland vegetation, and the reflection spectrum of the reed can predict TN concentration more accurately than that of cattail. The finding not only provides solid evidence for the potential application of remote sensing to detect water eutrophication but also enhances our understanding of the monitoring and management of water quality in urban wetlands using recycled water.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nitrogen Inversion Model in a Wetland Environment Based on the Canopy Reflectance of Emergent Plants

Zhao

Zhu

et al. 2022

Advances in Meteorology

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“…[28]. The spring (3)(4)(5), summer (6)(7)(8), autumn (9)(10)(11), growing season (4-10), and interannual NDVI data were acquired using the mean value synthesis method [29,30]. In prior investigations [31,32], the NDVI of the site was categorized into areas with low vegetation cover (less than 0.1), areas with medium-low vegetation cover (0.1-0.2), areas with medium vegetation cover (0.2-0.3), areas with medium-high vegetation cover (0.3-0.4), and areas with high vegetation cover (0.4-0.7).…”

Section: Data Preparationmentioning

confidence: 99%

Spatio-Temporal Dynamics of Normalized Difference Vegetation Index and Its Response to Climate Change in Xinjiang, 2000–2022

Zhang,

Gu,

Liu

et al. 2024

Forests

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Based on the NDVI and climate data from 2000 to 2022, this study systematically investigated the spatial and temporal patterns, trend characteristics, and stability of the NDVI in Xinjiang using the one-way linear regression method, Theil–Sen Median trend analysis, the Mann–Kendall significance test, and the coefficient of variation. Meanwhile, the persistence of the NDVI distribution was analyzed by combining the trend results and Hurst index. Finally, partial correlation analysis was used to deeply explore the response mechanisms of interannual and seasonal-scale NDVI and climatic factors in Xinjiang, and the characteristics of multi-year vegetation distribution were comprehensively analyzed with the help of human footprint data. The findings indicate the following: (1) The NDVI of interannual and seasonal vegetation in Xinjiang showed a significant increasing trend during the 23-year period, but the spatial distribution was heterogeneous, and the improvement of the vegetation condition in the southern part of the region was remarkable. (2) The NDVI is relatively stable across the region. Unlike in other regions, in general, it is difficult to maintain the existing trend in NDVI in the study area for a long period of time, and the reverse trend is more persistent. (3) On the interannual scale, both precipitation and temperature are positively correlated with the NDVI, and the influence of temperature (80.94%) is greater than that of precipitation (63.82%). Precipitation was dominantly positively correlated with the NDVI in spring, summer, and the growing season, while it was negatively correlated with it in autumn. Temperature and NDVI were positively correlated, with the greatest influence in the spring. (4) Human activities had the greatest impact on the areas with low vegetation cover and areas with medium–low vegetation cover, and there was a high degree of overlap between the areas where the interannual human footprints and NDVI showed an increasing trend. The percentage of human footprints that significantly correlated with interannual NDVI was 34.79%. In the future, the protection and management of ecologically fragile areas should be increased to increase desert-vegetation cover.

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“…Fractional vegetation cover (FVC) is an important ecological parameter for environmental assessment (Gitelson et al, 2002;Jia, 2013), and also usually used as an effective indicator to measure the condition and degree of vegetation on the surface (Song et al, 2023), which is also employed to monitor soil salinization, soil erosion and land sandy desertification (Shoshana et al,1996;Steffen, 2003;Godínez-Alvarez et al, 2009;Jing et al, 2011). The study of FVC can provide basic data to reveal the law of spatial differentiation of land surface, explore the driving factors of change, and analyze and evaluate the quality of regional ecological environment (Chen et al, 2022), widely applicating in agriculture, resources, land, disasters and other fields (Zhao et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…In the last decade, there are relatively few studies on the environmental changes of vegetation in the Jungar Banner, mostly focusing on the Jungar mining area (Liu et al, 2019;Bi & Liu 2022). The quantification of vegetation cover and change is a key feature to reflect environmental and ecological changes, which can provide basic information for assisting in the strategic planning of economic growth and avoiding additional environmental degradation, and maintaining current ecological areas with highquaility ( Jia et al, 2013;Gurnell et al, 2016;Liu et al, 2016;Yang et al, 2021). And, climate change will inevitably affect the growth environment of plants, and the growth state of plants (Buitenwerf et al, 2015;Verbeeck & Kearsley 2015;.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal Changes and Attribution of Vegetation in the Jungar Banner of Inner Mongolia During 2010 to 2022

Wang,

Ji,

Xue

et al. 2023

Preprint

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Fractional vegetation cover (FVC) is an important feature of the ecosystem, which reflects the ecological degeneration and restoration in the semi-arid areas. In this study, the spatio-temporal FVC changes were quantitatively evaluated from 2010 to 2022 in Jungar Banner of Inner Mongolia, China. Theil-Sen slope estimator and Mann-Kendall algorithm were used to monitor the spatio-temporal change trend of the FVC. Then, Hurst exponent and Theil-Sen Slope were integrated to evaluate the consistency of FVC change and predict its spatiotemporal evolution trend. Finally, we used correlation analysis to determine the association between FVC and other factors, such as terrain, temperature and precipitation. These results demonstrated that the condition of FVC in the Jungar Banner is good which was predominated by medium-low and medium FVC. The area with increasing FVC was little smaller than that with decreased FVC, but the decreased area was mainly dominated by no significant decrease. However, the Kubuqi Dessert, Yellow River, Loess plateau and mining areas accounted for the majority of the degraded areas. At present, the 42.7% of Jungar Banner appeared improved in the FVC, while the 57.3% appeared the degradation in the FVC, but the area of degradation was mainly slightly degraded in the future. In addition, the terrain and mining activity in Jungar Banner had a significant impact on the spatio-temporal distribution of FVC. This work will provide basic data and information for the future ecological development of Jungar Banner.

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Driving factor analysis on the vegetation changes derived from the Landsat TM images in Beijing

Cited by 7 publications

References 0 publications

Nitrogen Inversion Model in a Wetland Environment Based on the Canopy Reflectance of Emergent Plants

Nitrogen Inversion Model in a Wetland Environment Based on the Canopy Reflectance of Emergent Plants

Spatio-Temporal Dynamics of Normalized Difference Vegetation Index and Its Response to Climate Change in Xinjiang, 2000–2022

Spatio-temporal Changes and Attribution of Vegetation in the Jungar Banner of Inner Mongolia During 2010 to 2022

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