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Quantitative Assessment of the Impact of Physical and Anthropogenic Factors on Vegetation Spatial-Temporal Variation in Northern Tibet. REMOTE SENSING 2019. [DOI: 10.3390/rs11101183] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The alpine grassland on the Qinghai-Tibet Plateau covers an area of about 1/3 of China’s total grassland area and plays a crucial role in regulating grassland ecological functions. Both environmental changes and irrational use of the grassland can result in severe grassland degradation in some areas of the Qinghai-Tibet Plateau. However, the magnitude and patterns of the physical and anthropogenic factors in driving grassland variation over northern Tibet remain debatable, and the interactive influences among those factors are still unclear. In this study, we employed a geographical detector model to quantify the primary and interactive impacts of both the physical factors (precipitation, temperature, sunshine duration, soil type, elevation, slope, and aspect) and the anthropogenic factors (population density, road density, residential density, grazing density, per capita GDP, and land use type) on vegetation variation from 2000 to 2015 in northern Tibet. Our results show that the vegetation index in northern Tibet significantly decreased from 2000 to 2015. Overall, the stability of vegetation types was sorted as follows: the alpine scrub > the alpine steppe > the alpine meadow. The physical factors, rather than the anthropogenic factors, have been the primary driving factors for vegetation dynamics in northern Tibet. Specifically, meteorological factors best explained the alpine meadow and alpine steppe variation. Precipitation was the key factor that influenced the alpine meadow variation, whereas temperature was the key factor that contributed to the alpine steppe variation. The anthropogenic factors, such as population density, grazing density and per capita GDP, influenced the alpine scrub variation most. The influence of population density is highly similar to that of grazing density, which may provide convenient access to simplify the study of the anthropogenic activities in the Tibet plateau. The interactions between the driving factors had larger effects on vegetation than any single factor. In the alpine meadow, the interaction between precipitation and temperature can explain 44.6% of the vegetation variation. In the alpine scrub, the interaction between temperature and GDP was the highest, accounting for 27.5% of vegetation variation. For the alpine steppe, the interaction between soil type and population density can explain 29.4% of the vegetation variation. The highest value of vegetation degradation occurred in the range of 448–469 mm rainfall in the alpine meadow, 0.61–1.23 people/km2 in the alpine scrub and –0.83–0.15 °C in the alpine steppe, respectively. These findings could contribute to a better understanding of degradation prevention and sustainable development of the alpine grassland ecosystem in northern Tibet.
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The Global Land Surface Satellite (GLASS) Remote Sensing Data Processing System and Products. REMOTE SENSING 2013. [DOI: 10.3390/rs5052436] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Qin Z, Su GL, Zhang JE, Ouyang Y, Yu Q, Li J. Identification of important factors for water vapor flux and CO2 exchange in a cropland. Ecol Modell 2010. [DOI: 10.1016/j.ecolmodel.2009.11.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Trishchenko AP, Fedosejevs G, Li Z, Cihlar J. Trends and uncertainties in thermal calibration of AVHRR radiometers onboard NOAA‐9 to NOAA‐16. ACTA ACUST UNITED AC 2002. [DOI: 10.1029/2002jd002353] [Citation(s) in RCA: 50] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
| | - Gunar Fedosejevs
- Canada Centre for Remote Sensing Natural Resources Canada Ottawa Ontario Canada
| | - Zhanqing Li
- Earth System Science Interdisciplinary Center University of Maryland College Park Maryland USA
| | - Josef Cihlar
- Canada Centre for Remote Sensing Natural Resources Canada Ottawa Ontario Canada
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López G, Rubio M, Martı́nez M, Batlles F. Estimation of hourly global photosynthetically active radiation using artificial neural network models. AGRICULTURAL AND FOREST METEOROLOGY 2001; 107:279-291. [PMID: 0 DOI: 10.1016/s0168-1923(01)00217-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
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Goetz SJ, Prince SD, Goward SN, Thawley MM, Small J, Johnston A. Mapping net primary production and related biophysical variables with remote sensing: Application to the BOREAS region. ACTA ACUST UNITED AC 1999. [DOI: 10.1029/1999jd900269] [Citation(s) in RCA: 34] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Sellers PJ, Hall FG, Kelly RD, Black A, Baldocchi D, Berry J, Ryan M, Ranson KJ, Crill PM, Lettenmaier DP, Margolis H, Cihlar J, Newcomer J, Fitzjarrald D, Jarvis PG, Gower ST, Halliwell D, Williams D, Goodison B, Wickland DE, Guertin FE. BOREAS in 1997: Experiment overview, scientific results, and future directions. ACTA ACUST UNITED AC 1997. [DOI: 10.1029/97jd03300] [Citation(s) in RCA: 376] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Cihlar J, Chen J, Li Z. Seasonal AVHRR multichannel data sets and products for studies of surface-atmosphere interactions. ACTA ACUST UNITED AC 1997. [DOI: 10.1029/97jd01195] [Citation(s) in RCA: 39] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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