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NDVI-Derived Vegetation Trends and Driving Factors in West African Sudanian Savanna
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作者 Benewindé J.-B. Zoungrana Kangbeni Dimobé 《American Journal of Plant Sciences》 2023年第10期1130-1145,共16页
The Sudanian savanna is a key vegetation biome in West Africa providing food and vital ecosystem services. Recently, it has been reported alarming vegetation loss in this biome, calling for more investigation, relevan... The Sudanian savanna is a key vegetation biome in West Africa providing food and vital ecosystem services. Recently, it has been reported alarming vegetation loss in this biome, calling for more investigation, relevant to tackle land degradation and ensure food security. However, vegetation dynamics in this area remains a matter of debate, and one of the main challenges is to document consistently the underlying driving factors. This study aimed at assessing vegetation trends and driving factors from 2000 to 2022. NDVI trend, detected using the Mann-Kendall’s monotonic trend test, was used as proxy to express vegetation dynamics. In addition to the non-parametric Spearman correlation analysis, variables importance scores, derived from Random Forest (RF) classifications, were used to determine key driving factors among climatic, topographic, edaphic, accessibility and demographic factors. During 2000-2022, no significant trends largely characterised the vegetation cover of the study area. However, patterns of strong (weak) browning and strong (weak) greening affected 7.1% (10.6%) and 12.8% (19.1%) of the study area respectively. According to the driving factors analysis, the observed vegetation trends were mainly driven by rainfall dynamics (trend and mean annual), population growth and anthropogenic activities. The results of this study can support the development of efficient strategies for safeguarding vegetation cover in the Sudanian savanna of Burkina Faso. 展开更多
关键词 vegetation trends NDVI Sudanian Savanna Burkina Faso West Africa
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Comparing Land Degradation and Regeneration Trends in China Drylands 被引量:2
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作者 Gabriel Del BARRIO Zhihai GAO +6 位作者 Jaime Martinez-VALDERRAMA Xiaosong LI Maria ESANJUAN Bin SUN Alberto RUIZ Bengyu WANG Juan PUIGDEFABREGAS 《Journal of Geodesy and Geoinformation Science》 2020年第4期89-97,共9页
The aim of this paper is to offer a statistically sound method to make a precise account of the speed of land degradation and regeneration processes.Most common analyses of land degradation focus instead on the extent... The aim of this paper is to offer a statistically sound method to make a precise account of the speed of land degradation and regeneration processes.Most common analyses of land degradation focus instead on the extent of degraded areas,rather than on the intensity of degradation processes.The study was implemented for the Potential Extent of Desertification in China(PEDC),composed by arid,semi-arid,and dry sub-humid regions and refers to the period 2002 to 2012.The metrics were standard partial regression coefficients from stepwise regressions,fitted using Net Primary Productivity as the dependent variable,and year number and aridity as predictors.The results indicate that:①the extension of degrading lands(292896 km 2 or 9.12%of PEDC)overcomes the area that is recovering(194560 km 2 or 6.06%of PEDC);and②the intensity of degrading trends is lower than that of increasing trends in three land cover types(grassland,desert,and crops)and in two aridity levels(semi-arid and dry sub-humid).Such an outcome might pinpoint restoration policies by the Chinese government,and document a possible case of hysteresis. 展开更多
关键词 land degradation Potential Extent of Desertification in China environmental monitoring vegetation temporal trends standard partial regression coefficients
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