Vegetation dynamics of Zimbabwe investigated using NOAA-AVHRR NDVI from 1982 to 2006: a principal component analysis

Mberego, Seth; Kazadi, Sanga-Ngoie; Kobayashi, Shoko

doi:10.1080/01431161.2013.806833

Cited by 13 publications

(10 citation statements)

References 36 publications

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“…The number of simplified components ideal for determining the variation ought to be more than 70% [18,50,53]. Details on implementing PCA can be found in many studies, e.g., [17,18,25,31,34,36,51].…”

Section: Principal Component Analysismentioning

confidence: 99%

“…Climate change is an important factor in the African economy, and it indicates high spatial and temporal variabilities at different scales [34]. Despite the fact that atmospheric factors like temperature, relative humidity and pressure demonstrate variability in both area and height, precipitation shows high variability in both space and time [3,5,22,42].…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal dynamics of rainfall in Upper East Region of Ghana, West Africa, 1981–2016

et al. 2020

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There has been an increasing concern about effects of global warming on rainfall. Negative impacts on rainfall affect the environment and socio-economic activities of nations, globally. Rainfall characteristics at the Upper East Region (UER) of Ghana in terms of temporal and spatial variability are investigated from 1981 to 2016 using rainfall data from Ghana Meteorological Agency (GMet) and Climate Hazards Group Infrared Precipitation with Station. Using cumulative residual analysis, Mann-Kendall (MK), Sen's slope, wavelet transform (WT) and principal component analysis (PCA) tests, the rainfall variability in UER was examined. Results showed that 1981, 1999, 2002 and 2013 were years of major changes in rainfall variation. The MK and Sen's slope showed that 55.71% of UER have decreasing monthly rainfall with 27.34% significant trend. Months April, May and June showed decreasing rainfall trends. Months July, August and September showed significant increasing rainfall trend. WT revealed a significant variation in the annual rainfall. PCA revealed that the spatial variability of rainfall in UER is very diverse with 33.76% of the variability located in the northeastern part. The findings serve as benchmark in providing in-depth understanding of rainfall variation in UER for water resource managers, agriculturalists and drought mitigation.

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Section: Principal Component Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatiotemporal dynamics of rainfall in Upper East Region of Ghana, West Africa, 1981–2016

et al. 2020

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“…Climatic variability is a key factor influencing African economy and it demonstrates high spatial and temporal varieties at various time scale (Mberego et al, 2013). Despite the fact that atmosphere factors, such as, temperature, soil moisture, relative humidity and wind indicated variation on both spatial and temporal scale.…”

Section: Introductionmentioning

confidence: 99%

Assessing Spatial and Temporal Precipitation Dynamics in Upper East Region of Ghana Using Chirps Data from 1981 to 2016

Okrah

Quaye‐Ballard

Andam-Akorful

et al. 2019

International Journal of Geography and Geology

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Cumulative residual analysis (CRA) Mann-Kendall and Sen's Slope tests Wavelet transform (WT) Principal component analysis (PCA) Remote sensing Ghana CHIRPS data.Precipitation variability evaluation assumes a vital part in water asset administration and rainfed agribusiness. In Ghana, rain gauge stations are poorly distributed and also, obtaining long time span of data is difficult due to data inconsistency, as a result remotely sensed precipitation products are largely used to complement ground gauge stations data for assessing climatic variability and water resource managements. In this study, Climate Hazards Group Infrared Precipitation with Station (CHIRPS) precipitation data from 1981-2016 and also utilizing Cumulative Residual Analysis (CRA), Mann-Kendall, Sen's Slope, Wavelet Transform (WT) and Principal Component Analysis (PCA). Results show that 1981, 1999, 2002 and 2013 were four noteworthy years with changes in precipitation. The Mann-Kendal and Sen's Slope demonstrate that 55.71% of UER indicated diminishing month to month precipitation with 27.34% critical patterns. Precipitation in April, May, and June demonstrated a diminishing pattern while July, August, and September showed an increasing trend during the 35 years' study period. Further investigation using Continuous Wavelet Transform indicated an annual variation significant. PCA uncovered that the spatial variability of precipitation in UER is extremely assorted, however greater part (33.76%) of the fluctuation is situated in the north-eastern part. Thus, the results from remotely sensed precipitation products an effective, efficient and cheap way of assessing top to the bottom comprehension of precipitation variation at regional level. Contribution/Originality: This study is one of very few studies which have investigated in the study area which applied new methods such as Cumulative residual analysis (CRA), Mann-Kendall and Sen's Slope tests, Wavelet transform (WT), Principal component analysis (PCA) on remotely sensed precipitation data to assess both spatial and temporal variability.

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“…For natural reasons such as climate change, or through anthropogenic change such as agricultural activity, the seasonal dynamics of vegetation cover have been considerably affected in recent decades in West Africa. However, the lack of long-term data has hitherto prevented detailed investigation of climate-vegetation and spatio-temporal relationships at regional scales (Chamaille-Jammes et al, 2006), although such knowledge could help understand climate variability and lead to improved seasonal forecasting ability and predictions of ecosystem responses to climate change (Philippon et al, 2007;Mberego et al, 2013). In this context, the AMMA (African Monsoon Multidisciplinary Analysis) Program was tasked with long-term observation of the West African monsoon and its features with the aim of assessing hydrological impacts of climatic or anthropogenic changes (Redelsperger et al, 2006;Lebel et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Changes in www.ijrsa.org International Journal of Remote Sensing Applications Volume 4 Issue 3, September 2014 phenological events can be identified and classified year-to-year for different land-cover types (Roehrig et al, 2005). The most common and reliable index for studying vegetation activity is NDVI (Normalized Difference Vegetation Index), which has been shown to be associated with biomass and photosynthetic activity (Gurgel et al, 2003;Rigina and Rasmussen, 2003;Lasaponara , 2006;Fensholt et al, 2011;Miranda-Aragón et al, 2012;Mberego et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Vegetation Activity in the Upper Oueme Basin (Benin, Africa) Studied from SPOT-VGT (2002-2012) According to Land Cover

Do¹,

Bigot²,

Galle³

2014

International Journal of Remote Sensing Applications

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Signs of climate change in West Africa over the last few decades are among the significant observed in the tropics, in particular the decrease in mean annual precipitation. Although such change has brought about new eco-climatic constraints on vegetation forms, it has not proven easy to determine interannual and intra-seasonal variations on a regional scale for major vegetation forms, whether natural or highly artificial as a result of human activities. The present study analyzes vegetation activity via a Normalized Difference Vegetation Index (NDVI) defined from ten-day SPOT-VGT data (one-km resolution, covering the period from 2002 to 2012) in the African Monsoon Multidisciplinary Analysis (AMMA) Program observation zone, located in the Upper Oueme River Basin in Benin. The statistical analysis is mainly based on a multifactor approach allowing approximately 54% of interannual NDVI variations to be accounted for. Results show that spatio-temporal NDVI variability in the River Basin is highly dependent on land use, be it forest, wooded savanna, farmland or areas undergoing conversion.

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Vegetation dynamics of Zimbabwe investigated using NOAA-AVHRR NDVI from 1982 to 2006: a principal component analysis

Cited by 13 publications

References 36 publications

Spatiotemporal dynamics of rainfall in Upper East Region of Ghana, West Africa, 1981–2016

Spatiotemporal dynamics of rainfall in Upper East Region of Ghana, West Africa, 1981–2016

Assessing Spatial and Temporal Precipitation Dynamics in Upper East Region of Ghana Using Chirps Data from 1981 to 2016

Vegetation Activity in the Upper Oueme Basin (Benin, Africa) Studied from SPOT-VGT (2002-2012) According to Land Cover

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