Drought is a key challenge of third world countries whose economies are based on agriculture. Also, lack of rainfall plays a major role in exacerbating climate change. Drought is resulting in a decline in vegetation greenness and plant mortality specifically in semi-arid region. In this study, satellite-based drought assessment was used to characterize drought, and its impact on forest in semi-arid region of Ethiopia. Drought severity and forest cover change were detected over the period between 2014, and 2022 using geographic information system and remote sensing techniques. Vegetation condition index (VCI) and normalized difference vegetation index (NDVI) are used to detect drought severity over the past decades. Results show that 2015, 2017, 2019and 2022 were the most drought years. The spatial forest covers is significantly decreased during severe drought years. Minimum dense forest was observed in 2017and 2019 over spatial extend of 0.80 ha and 124.6 ha, respectively during drought years. To evaluate how precipitation deficit affect forest function, simple linear regression is performed. Result of (R2 = 0.49 and P = 0.05) indicate that, nearly 50% of forest greenness is influenced by precipitation deficit. This study suggested that remote sensing indices are very crucial to characterize drought pattern at small “scale” particularly in assessment of drought impact on forest resource.
Drought is a key challenge for third-world countries whose economies are based on agriculture. Also, lack of rainfall plays a major role in accelerating climate change. Drought is resulting in a decline in vegetation greenness and plant mortality specifically in the semi-arid region. In this study, satellite-based drought assessment was used to characterize drought and its impact on forests in the semi-arid regions of Ethiopia. Drought severity and forest cover change were detected over the period between 2014 and 2022 Using geographic information systems and remote sensing techniques. Vegetation condition index (VCI) and Normalized difference vegetation index (NDVI) were used to detect drought severity in the present study. Results of this study showed that 2017, 2015, 2022 and 2019 were the most drought years. The forest resource is significantly decreased during severe drought years. The Minimum dense forest was observed in 2017 and 2015 over a spatial extent of 193 ha and 217 ha respectively during drought years. To evaluate how precipitation deficit affects forest function, simple linear regression is performed. Results of this linear regression “R2 = 0.49 and P = 0.05” indicated that nearly 50% of forest greenness is influenced by precipitation deficit. This study suggested that remote sensing indices are very crucial to characterize drought patterns at a small “scale”, particularly in the assessment of drought impact on forest resources. Article Highlights Satellite indices like NDVI and VCI help to monitor the drought impact on forest cover. When severe drought is occurred along with precipitation deficit, the forest cover is decreased. Remote sensing data provide clear information for decision-making regarding drought's impact on the forest.
Drought is a key challenge of third world countries whose economies are based on agriculture. Also, lack of rainfall plays a major role in exacerbating climate change. Drought is resulting in a decline in vegetation greenness and plant mortality specifically in semi-arid region. In this study, satellite-based drought assessment was used to characterize drought, and its impact on forest in semi-arid region of Ethiopia. Drought severity and forest cover change were detected over the period between 2014, and 2022 using geographic information system and remote sensing techniques. Vegetation condition index (VCI) and normalized difference vegetation index (NDVI) are used to detect drought severity over the past decades. Results show that 2015, 2017, 2019and 2022 were the most drought years. The spatial forest covers is significantly decreased during severe drought years. Minimum dense forest was observed in 2017and 2019 over spatial extend of 0.80 ha and 124.6 ha, respectively during drought years. To evaluate how precipitation deficit affect forest function, simple linear regression is performed. Result of (R2=0.49 and P=0.05) indicate that, nearly 50% of forest greenness is influenced by precipitation deficit. This study suggested that remote sensing indices are very crucial to characterize drought pattern at small “scale” particularly in assessment of drought impact on forest resource.
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