2001—2020年埃及植被生长状况时空变化特征

doi:10.11707/j.1001-7488.LYKX20210566

Abstract

Abstract:

Objective: In order to scientifically evaluate the results of desertification prevention and control in Egypt, in-depth study of the temporal and spatial characteristics of vegetation growth in Egypt in the past 20 years, and at the same time provide a scientific basis for the systematic evaluation of Egypt’s desertification prevention and control and sustainable development. Method: Based on MODIS-EVI data from 2001 to 2020, the harmonic analysis of time series is used to reconstruct the data, trend analysis, coefficient of variation and Hurst index were used for the analysis of temporal and spatial characteristics of vegetation growth in Egypt in the past 20 years and its future trends. Result: 1） The growth curve of vegetation in Egypt during the year is characterized by double peaks. In the past 20 years, vegetation growth in Egypt has tended to improve, with the average growth rate of EVI being 0.000 31?a^?1. 2） The areas with stable vegetation growth in Egypt accounted for 93.21% of the total area, mainly distributed in most areas of western, central, and southern Egypt; the areas with improved vegetation growth accounted for 4.79% of the total area, mainly distributed in the northwest coast of Egypt, east and west of the Nile Delta Department; the areas with decreasing vegetation growth accounted for 2.00% of the total area, mainly distributed in the central part of the Nile Delta. 3） The coefficient of variation of vegetation growth in Egypt has been relatively low in the past 20 years, while the fluctuations in vegetation growth in the Nile Delta and the Nile River coast areas are relatively obvious. 4） The reverse changes of future vegetation growth in Egypt are stronger than the changes in opposite direction. The area of vegetation improvement in the future will account for 3.74% of the total area, and the area of vegetation degraded in the future will account for 3.05% of the total area. Conclusion: In the past 20 years, Egypt has made remarkable achievements in the prevention and control of desertification. The growth of vegetation tends to improve in general, and it will show a certain degree of sustainability in the future.

Key words: vegetation index, spatiotemporal variations, coefficient of variation, Hurst index, Egypt

CLC Number:

S718.54
TP79

Chenyang He,Feng Yan,Qi Lu,Yan Jiao. Characterization of Spatiotemporal Variations in Vegetation Growth in Egypt in 2001—2020[J]. Scientia Silvae Sinicae, 2023, 59(3): 65-72.

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References 0

	郭紫晨, 刘树林, 康文平, 等 2000—2015年毛乌素沙区植被覆盖度变化趋势. 中国沙漠, 2018, 38 (5): 203- 211.
	Guo Z C, Liu S L, Kang W P, et al Change trend of vegetation coverage in the Mu Us sandy region from 2000 to 2015. Journal of Desert Research, 2018, 38 (5): 203- 211.
	李双双, 延军平, 万　佳近10年陕甘宁黄土高原区植被覆盖时空变化特征. 地理学报, 2012, 67 (7): 960- 970. doi: 10.11821/xb201207009
	Li S S, Yan J P, Wan J The spatial-temporal changes of vegetation restoration on Loess Plateau in Shaanxi-Gansu-Ningxia region. Acta Geographica Sinica, 2012, 67 (7): 960- 970. doi: 10.11821/xb201207009
	王瑞杰, 闫　峰 2000—2018年西北砒砂岩区植被覆盖度与地形效应. 应用生态学报, 2020, 31 (4): 1194- 1202. doi: 10.13287/j.1001-9332.202004.005
	Wang R J, Yan F Fractional vegetation cover and topographic effects in Pisha sandstone area of northwest China in 2000—2018. Chinese Journal of Applied Ecology, 2020, 31 (4): 1194- 1202. doi: 10.13287/j.1001-9332.202004.005
	闫　峰, 卢　琦, 吴　波, 等 1981—2015年新疆生产建设兵团植被生长变化特征. 干旱区地理, 2018, 41 (3): 121- 131.
	Yan F, Lu Q, Wu B, et al Characteristics of vegetation growth in Xinjiang Production and Construction Corps in 1981—2015. Arid Land Geography, 2018, 41 (3): 121- 131.
	闫　峰, 王艳姣基于Ts-EVI特征空间的土壤水分估算. 生态学报, 2009a, 29 (9): 4884- 4891.
	Yan F, Wang Y J Estimation of soil moisture from Ts-EVI feature space. Acta Ecologica Sinica, 2009a, 29 (9): 4884- 4891.
	闫　峰, 王艳姣, 武建军, 等基于Ts-EVI时间序列谱的冬小麦面积提取. 农业工程学报, 2009b, 25 (4): 135- 140.
	Yan F, Wang Y J, Wu J J, et al Extracting winter wheat area using temporal sequence of Ts-EVI. Transactions of the Chinese Society of Agricultural Engineering, 2009b, 25 (4): 135- 140.
	闫　峰, 吴　波, 王艳姣 2000—2011年毛乌素沙地植被生长状况时空变化特征. 地理科学, 2013, 33 (5): 602- 608.
	Yan F, Wu B, Wang Y J Spatial and temporal variations of vegetation growth status in Mu Us sandy land in 2000—2011. Scientia Geographica Sinica, 2013, 33 (5): 602- 608.
	杨　强, 王婷婷, 陈　昊, 等基于MODIS EVI数据的锡林郭勒盟植被覆盖度变化特征. 农业工程学报, 2015, 31 (22): 191- 198. doi: 10.11975/j.issn.1002-6819.2015.22.026
	Yang Q, Wang T T, Chen H, et al Characteristics of vegetation cover change in Xilin Gol League based on MODIS EVI data. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31 (22): 191- 198. doi: 10.11975/j.issn.1002-6819.2015.22.026
	殷　贺, 李正国, 王仰麟, 等基于时间序列植被特征的内蒙古荒漠化评价. 地理学报, 2011, 66 (5): 653- 661. doi: 10.11821/xb201105008
	Yin H, Li Z G, Wang Y L, et al Assessment of desertification using time series analysis of hyper-temporal vegetation indicator in Inner Mongolia. Acta Geographica Sinica, 2011, 66 (5): 653- 661. doi: 10.11821/xb201105008
	左丽君, 张增祥, 董婷婷, 等 MODIS/NDVI和MODIS/EVI在耕地信息提取中的应用及对比分析. 农业工程学报, 2008, 24 (3): 167- 172. doi: 10.3321/j.issn:1002-6819.2008.03.034
	Zuo L J, Zhang Z X, Dong T T, et al Application of MODIS/NDVI and MODIS EVI to extracting the information of cultivated land and comparison analysis. Transactions of the Chinese Society of Agricultural Engineering, 2008, 24 (3): 167- 172. doi: 10.3321/j.issn:1002-6819.2008.03.034
	Chen J H, Yan F, Lu Q Spatiotemporal variation of vegetation on the Qinghai–Tibet Plateau and the influence of climatic factors and human activities on vegetation trend (2000—2019). Remote Sensing, 2020, 12 (19): 3150. doi: 10.3390/rs12193150
	Evans J, Geerken R Discrimination between climate and human-induced dryland degradation. Journal of Arid Environments, 2004, 57 (4): 535- 554. doi: 10.1016/S0140-1963(03)00121-6
	Fensholt R, Langanke T, Rasmussen K, et al Greenness in semi-arid areas across the globe 1981—2007 : an Earth Observing Satellite based analysis of trends and drivers. Remote Sensing of Environment, 2012, 121, 144- 158. doi: 10.1016/j.rse.2012.01.017
	Hammam A A, Mohamed E S, 2020. Mapping soil salinity in the East Nile Delta using several methodological approaches of salinity assessment. The Egyptian Journal of Remote Sensing and Space Science, 23(2): 125–131.
	Hereher M E. 2017. Effect of land use/cover change on land surface temperatures−The Nile Delta, Egypt. Journal of African Earth Sciences. 126: 75–83.
	Huete A, Didan K, Miura T, et al. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83(1/2): 195–213.
	Hurst H E. 1951. Long-term storage capacity of reservoirs. Transactions of the American Society of Civil Engineers, 116(1): 770–799.
	John R, Chen J Q, Lu N, et al Predicting plant diversity based on remote sensing products in the semi-arid region of Inner Mongolia. Remote Sensing of Environment, 2008, 112 (5): 2018- 2032. doi: 10.1016/j.rse.2007.09.013
	Olsson L, Eklundh L, Ardö J A recent greening of the Sahel-trends, patterns and potential causes. Journal of Arid Environments, 2005, 63 (3): 556- 566. doi: 10.1016/j.jaridenv.2005.03.008
	Roerink G J, Menenti M, Verhoef W Reconstructing cloudfree NDVI composites using fourier analysis of time series. International Journal of Remote Sensing, 2000, 21 (9): 1911- 1917. doi: 10.1080/014311600209814
	UNCCD. 1998. United Nations convention to combat desertification in countries experiencing serious drought and/or desertification, particularly in Africa. UNCCD Secretariat, Bonn, Available at http://www.unccd.int.
	Wang R J, Yan F, Wang Y J, 2020. Vegetation growth status and topographic effects in the Pisha Sandstone area of China. Remote Sensing, 12(17): 2759.
	Yan F, Wu B, Wang Y J Estimating aboveground biomass in Mu Us Sandy Land using Landsat spectral derived vegetation indices over the past 30 years. Journal of Arid Land, 2013, 5 (4): 521- 530. doi: 10.1007/s40333-013-0180-0
	Yan F, Wu B, Wang Y J Estimating spatiotemporal patterns of aboveground biomass using Landsat TM and MODIS images in the Mu Us Sandy Land, China. Agricultural and Forest Meteorology, 2015, 200, 119- 128. doi: 10.1016/j.agrformet.2014.09.010
	Yassen A N, Nam W H, Hong E M Impact of climate change on reference evapotranspiration in Egypt. Catena, 2020, 194, 104711. doi: 10.1016/j.catena.2020.104711

编号 No.	等级Level	面积Area/ km²	比例 Proportion (%)
?5	特重度波动退化区	6 049.50	0.68
?5	Extremely severe fluctuation degradation area	6 049.50	0.68
?4	重度波动退化区	4 412.63	0.50
?4	Severe fluctuation degradation area	4 412.63	0.50
?3	中度波动退化区	5 417.00	0.61
?3	Moderate fluctuation degradation area	5 417.00	0.61
?2	轻度波动退化区	1 538.43	0.17
?2	Mild fluctuation degradation area	1 538.43	0.17
?1	正常波动退化区	245.63	0.03
?1	Normal fluctuation degradation area	245.63	0.03
0	稳定区	823 189.81	93.21
0	Stable area	823 189.81	93.21
1	正常波动改善区	781.56	0.09
1	Normal fluctuation improvement area	781.56	0.09
2	轻度波动改善区	2 333.44	0.26
2	Mild fluctuation improvement area	2 333.44	0.26
3	中度波动改善区	6 352.00	0.72
3	Moderate fluctuation improvement area	6 352.00	0.72
4	重度波动改善区	4 754.44	0.54
4	Severe fluctuation improvement area	4 754.44	0.54
5	特重度波动改善区	28 105.38	3.18
5	Extremely severe fluctuation improvement area	28 105.38	3.18

斜率 Slope (S)	H<0.5	H>0.5
S<?0.001	由退化到改善From degradation to improvement	持续退化Sustained and degradation
?0.001≤S≤0.001	持续稳定Sustained and stable	持续稳定Sustained and stable
S>0.001	由改善到退化From improvement to degradation	持续改善Sustained and improvement

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Characterization of Spatiotemporal Variations in Vegetation Growth in Egypt in 2001—2020

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