Assessing Long-Term Trends In Vegetation Productivity Change Over the Bani River Basin in Mali (West Africa)

Traoré, Souleymane Sidi; Landmann, Tobias; Forkuo, Eric Kwabena; Traoré, Pierre C. Sibiry

doi:10.15640/jges.v2n2a2

Cited by 14 publications

(13 citation statements)

References 37 publications

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“…Which is a non-parametric test that does not require normally distributed data for validity [ 65 ]. This test is widely used in studies of hydrological, climatological and NDVI time series [ 65 , 66 , 67 , 68 ], where the Kendall rank correlation coefficient (τ) ranges from −1 to +1, and the statistical significance is tested using the p -value. For the meteorological dataset, the minimum level of significance that was adopted was α = 0.01.…”

Section: Methodsmentioning

confidence: 99%

Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

Scottá

Fonseca

2015

Sensors

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This study aimed to evaluate changes in the aboveground net primary productivity (ANPP) of grasslands in the Pampa biome by using experimental plots and changes in the spectral responses of similar vegetation communities obtained by remote sensing and to compare both datasets with meteorological variations to validate the transition scales of the datasets. Two different geographic scales were considered in this study. At the local scale, an analysis of the climate and its direct influences on grassland ANPP was performed using data from a long-term experiment. At the regional scale, the influences of climate on the grassland reflectance patterns were determined using vegetation sensor imagery data. Overall, the monthly variations of vegetation canopy growth analysed using environmental changes (air temperature, total rainfall and total evapotranspiration) were similar. The results from the ANPP data and the NDVI data showed the that variations in grassland growth were similar and independent of the analysis scale, which indicated that local data and the relationships of local data with climate can be considered at the regional scale in the Pampa biome by using remote sensing.

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Section: Methodsmentioning

confidence: 99%

Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

Scottá

Fonseca

2015

Sensors

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“…A pair of Landsat MSS (10 November 1972) was downloaded from the same source at the path 207/row 053 and path 207/row 054. These data are acquired for the time corresponding to the early dry season onset (October to December), enabling the clear distinction between land use/cover (LUC) types, especially agricultural fields and typical savannahs in the landscape (Traore et al, 2014;Ruelland et al, 2010).…”

Section: Mapping the Land-use And Cover For The Period 1972-2014mentioning

confidence: 99%

Assessment of multifunctional landscapes dynamics in the mountainous basin of the Mo River (Togo, West Africa)

et al. 2017

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In this study, historical landscape dynamics were investigated to (i) map the land use/cover types for the years 1972, 1987, 2000 and 2014; (ii) determine the types and processes of landscape dynamics; and (iii) assess the landscape fragmentation and habitat loss over time. Supervised classification of multi-temporal Landsat images was used through a pixel-based approach. Post-classification methods included systematic and random change detection, trajectories analysis and landscape fragmentation assessment. The overall accuracies (and Kappa statistics) were of 68.86% (0.63), 91.32% (0.79), 90.66% (0.88) and 91.88% (0.89) for 1972, 1987, 2000 and 2014, respectively. The spatio-temporal analyses indicated that forests, woodlands and savannahs dominated the landscapes during the four dates, though constant areal decreases were observed. The most important dynamic process was the decline of woodlands with an average annual net loss rate of-2%. Meanwhile, the most important land transformation occurred during the transition 2000-2014, due to anthropogenic pressures. Though the most important loss of vegetation greenness occurred in the unprotected areas, the overall analyses of change indicated a declining trend of land cover quality and an increasing landscape fragmentation. Sustainable conservation strategies should be promoted while focusing restoration attention on degraded lands and fragmented ecosystems in order to support rural livelihood and biodiversity conservation.

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“…Elevation and slope can significantly influence the vegetation composition, distribution, and growth through soil moisture and fertility [68,69]. Pozzi and Small [70] and Traore et al [71] revealed a negative correlation between NDVI and population densities. However, there are some opposing views; Fuller and Gaston [14] showed that there was a long-term inverted N-shaped curve relationship between population growth and vegetation cover in a region with frequent human activities and that the influence of climate change on vegetation cover changes was relatively small.…”

Section: Discussionmentioning

confidence: 99%

Anthropogenic and Biophysical Factors Associated with Vegetation Restoration in Changting, China

Wang

Nizami

et al. 2018

Forests

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Changting has been promoted by the Chinese government as a demonstration for the soil and water conservation works in recent years. As the experience in Changting is now being explored and summarized and will be further promoted to the nation, it is important to understand the factors affecting the vegetation restoration process. Random forest and multiple linear regression approaches were applied to investigate the influential factors and their relative importance on the dynamic change of vegetation coverage of Changting during the period of 2000-2010. The Normalized Difference Vegetation Index (NDVI) was used to calculate Fractional Vegetation Cover (FVC) dynamics in response to topographic, climatic, infrastructure, and economic factors. The results show that overall, there was a dramatic increase in the FVC of Changting from 2000-2010. The percentage of the FVC-increased area reached 87.86% with an increase rate of 0.142. Factors such as precipitation, temperature, elevation, slope and financial investment for soil conservation were important drivers of local FVC change. Our findings reveal that climatic factors along with the strict implementation of government policies played a role in driving vegetation cover dynamics, and the continuation of implementation of soil erosion management in Changting is required.

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Assessing Long-Term Trends In Vegetation Productivity Change Over the Bani River Basin in Mali (West Africa)

Cited by 14 publications

References 37 publications

Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

Assessment of multifunctional landscapes dynamics in the mountainous basin of the Mo River (Togo, West Africa)

Anthropogenic and Biophysical Factors Associated with Vegetation Restoration in Changting, China

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