Mapping the Spatial-Temporal Dynamics of Vegetation Response Lag to Drought in a Semi-Arid Region

Drought, as an extreme climate event, affects the ecological environment for vegetation and agricultural production. Studies of the vegetative response to drought are paramount to providing scientific information for drought risk mitigation. In this paper, the spatial-temporal pattern of drought and the response lag of vegetation in Nebraska were analyzed from 2000 to 2015. Based on the long-term Daymet data set, the standard precipitation index (SPI) was computed to identify precipitation anomalies, and the Gaussian function was applied to obtain temperature anomalies. Vegetation anomaly was identified by dynamic time warping technique using a remote sensing Normalized Difference Vegetation Index (NDVI) time series. Finally, multilayer correlation analysis was applied to obtain the response lag of different vegetation types. The results show that Nebraska suffered severe drought events in 2002 and 2012. The response lag of vegetation to drought typically ranged from 30 to 45 days varying for different vegetation types and human activities (water use and management). Grasslands had the shortest response lag (~35 days), while forests had the longest lag period (~48 days). For specific crop types, the response lag of winter wheat varied among different regions of Nebraska (35–45 days), while soybeans, corn and alfalfa had similar response lag times of approximately 40 days

Drought events and their effects on vegetation productivity in China

Many parts of the world have experienced frequent and severe droughts during the last few decades. Most previous studies examined the effects of specific drought events on vegetation productivity. In this study, we characterized the drought events in China from 1982 to 2012 and assessed their effects on vegetation productivity inferred from satellite data. We first assessed the occurrence, spatial extent, frequency, and severity of drought using the Palmer Drought Severity Index (PDSI). We then examined the impacts of droughts on China\u27s terrestrial ecosystems using the Normalized Difference Vegetation Index (NDVI). During the period 1982–2012, China\u27s land area (%) experiencing drought showed an insignificant trend. However, the drought conditions had been more severe over most regions in northern parts of China since the end of the 1990s, indicating that droughts hit these regions more frequently due to the drier climate. The severe droughts substantially reduced annual and seasonal NDVI. The magnitude and direction of the detrended NDVI under drought stress varied with season and vegetation type. The inconsistency between the regional means of PDSI and detrended NDVI could be attributed to different responses of vegetation to drought and the timing, duration, severity, and lag effects of droughts. The negative effects of droughts on vegetation productivity were partly offset by the enhancement of plant growth resulting from factors such as lower cloudiness, warming climate, and human activities (e.g., afforestation, improved agricultural management practices)

Investigating the groundwater dependence and response to rainfall variability of vegetation in the Touws river and catchment using remote sensing

Magister Artium - MAChanges in climate patterns have raised concerns for environmentalists globally and across southern Africa. The changes greatly affect the growth dynamics of vegetation to such an extent that climate elements such as rainfall have become the most important determinant of vegetation growth. In arid and semi-arid environments, vegetation relies on near-surface groundwater as the main source of water. Changes in the environment due to climate can be examined by using remotely sensed data. This approach offers an affordable and easy means of monitoring the impact of climate variability on vegetation growth. This study examined the response of vegetation to rainfall and temperature, and assessed the dependence thereof on groundwater in a climatically variable region of the semi-arid Karoo. The methodology used included sampling plant species in the riparian and non-riparian areas over two plant communities in seven vegetation plots. The Normalised Difference Vegetation Index (NDVI) derived from the Landsat OLI and TM was used to measure vegetation productivity. This was compared with rainfall totals derived from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and the mean monthly temperature totals. A drought index, (Standardised Precipitation Index – SPI) was an additional analysis to investigate rainfall variability. Object-based Image Analysis (OBIA) and Maximum Likelihood supervised classification approaches together with indicators of groundwater discharge areas (Topographic Wetness Index – TWI, and profile curvature) were used to map vegetation and surface water that depend on groundwater

Significance of soil moisture on vegetation greenness in the African Sahel from 1982 to 2008

Popular science The Sahel is a semi-arid eco-climatic transition zone in northern Africa separating the Sahara desert from the Africa’s tropical forest. The Sahel word in Arabic language means “shore” which is linguistically describes the appearances of vegetation as a shoreline defining the boundary of the Sahara desert. Soil moisture (rainwater accumulated over a period of time in soil) is considered one of the most important factors on vegetation growth in Sahel as the agriculture droughts occurs due to soil moisture deficiency. The projected number of Africans in semi-arid locations will suffer from increasing water stress by 2020s is between 75-250 million and this number is projected to increase to be between 350-600 million by 2050s. This study aims to evaluate the relationship between soil moisture and vegetation growth in Sahel region during 1982-2008 at different time lags. Land cover and soil texture data were used to investigate whether the relationship between soil moisture and vegetation growth are related to land cover and soil type or not. Satellite remote sensing data (vegetation index), modelled soil moisture data land cover map and soil type map were mainly used to achieve the purpose of this study. The most important findings of this study is the best correlations between vegetation greenness and soil moisture occurred at lag0 (no time lag differences), lag1 (one month time lag) and lag2 (two months’ time lags). The correlation relationship varied between low and moderate values in Sahel region indicating that soil moisture variable is not only the main driver for vegetation dynamics in the study area and maybe other factors such as human impacts could have a great contribution on vegetation changes in Sahel. Croplands and Grasslands are the main land cover types that increasing the correlation relationship between soil moisture and vegetation growth, whereas Entisols (occur in flood plains and steep slopes) and Alfisols (occur under forest and mixed vegetation cover) are the main soil types showing a positive effect on the correlation relationship between soil moisture and vegetation dynamics. Finally, good understanding the temporal relationship between water availability and vegetation dynamics can help us to know water affects plant growth and to predict the future relationship within a season between vegetation growth and soil moisture which can be used for detecting famine possibilities.This study investigates the temporal correlation relationship between vegetation greenness and soil moisture in the African Sahel from 1982 to 2008 at different time lags (maximum five lags used in this study) and determines the extent which soil moisture explains vegetation dynamics in the Sahel. Monthly composites of remotely sensed Normalized Difference Vegetation Index (NDVI) from National Oceanic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (NOAA-AVHRR) were used in this study as a proxy for vegetation growth, whereas modeled soil moisture data (1.6m column depth) provided by the NOAA National Centers for Environmental Predictions (NCEP) Climate Prediction Center (CPC) Global Monthly high resolution Soil Moisture (GMSM) was used as an indicator of moisture availability for plants. The analyses were applied for all-year months data (dry season included) and only for growing months season (from July to October) to estimate the effect of long dry season on the association between vegetation growth and soil moisture. Trends in vegetation greenness, soil moisture and NDVI residuals were calculated separately in Sahel to investigate the changes occurred in vegetation growth and soil moisture during the study period. The correlations relationship were evaluated against land cover and soil texture data to estimate the influences of land cover and soil type on the strength of correlation relationship between vegetation growth and soil moisture. The results showed a significant correlation relationship between vegetation greenness and soil moisture at lag0 (no time lag differences), lag1 (one month time lag) and lag2 (two months’ time lag) with a better association in northern parts of Sahel region by using only the growing season data. However, the significant correlations covered a larger area by using all the year data (long dry season included). The results indicated that using AVHRR NDVI data for studying the vegetation growth in response to soil moisture availability is limited in the southern parts of the study area. The significant correlation coefficients (r) are varied between low and moderate values (0.1-0.6) in the study area, suggesting that soil moisture is not only the main driver of vegetation dynamics in Sahel. Vegetation greenness showed a significant increase during the study period in many locations in Sahel region (center of Chad, Senegal and south of Mali), whereas soil moisture showed a small significant locations in the study area (center of Sudan, center of Mali and east of Mauritania) during the study period from 1982-2008. Land cover type (Croplands and Grasslands) and soil texture (Entisols and Alfisols) showed a significant association and high influences on the correlation relationship between vegetation greenness and soil moisture at lag0, lag1 and lag2.Scientific abstract Soil moisture (rainwater accumulated over a period of time in soil) is considered one of the most important factors on vegetation growth in Sahel as the agriculture droughts usually associated with soil moisture deficiency. This thesis study investigates the correlation relationship between soil moisture and vegetation greenness in the Sahel region from 1982 to 2008 at different time lags (maximum five lags used in our analysis). Monthly time series data of remotely sensed Normalized Difference Vegetation Index (NDVI) from National Oceanic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (NOAA-AVHRR) was used in this study as a proxy for vegetation growth, whereas the monthly modeled soil moisture data was provided by the NOAA National Centers for Environmental Predictions (NCEP) Climate Prediction Center (CPC) Global Monthly high resolution Soil Moisture (GMSM). Land cover map and soil map data of Sahel region were used to investigate the effect of land cover and soil type on the correlation relationship. The results were based on pixel by pixel analysis for two time frames: all-year data (dry season included) and only growing season (from July to October). The best correlation between NDVI and soil moisture occurred at lag0 (no time lag difference), lag1 (one month time lag) and lag2 (two month time lag) and the strength of relationship is decreasing by increasing time lags (lag0, lag1 and lag2 are the dominant in the study area). The degree of association between NDVI and soil moisture increased in the northern part of Sahel region by using only the growing season data and this relationship was vague in central and southern part of Sahel region. The significant correlation coefficients varied between low and moderate (0.1-0.6) across the study area suggesting that soil moisture is not only the main driver factor on the vegetation dynamics in Sahel region. Trends of vegetation showed a significant increase during the study period in many locations (center of Chad, Senegal and south of Mali), whereas soil moisture showed small significant locations (center of Sudan, center of Mali and east of Mauritania) from 1982-2008. Land cover type (Croplands and Grasslands) and soil type (Entisols and Alfisols) showed a significant influence on the correlation relationship between vegetation greenness and soil moisture

Historical Perspectives on AVHRR NDVI and Vegetation Drought Monitoring

No abstract availabl

Drought impacts assessment in Brazil - a remote sensing approach

Climate extremes are becoming more frequent in Brazil; studies project an increase in drought occurrences in many regions of the country. In the south, drought events lead to crop yield losses affecting the value chain and, therefore, the local economy. In the northeast, extended periods of drought lead to potential land degradation, affecting the livelihood and hindering local development. In the southern Amazon, an area that experienced intense land use change (LUC) in the last, the impacts are even more complex, ranging from crop yield loss and forest resilience loss, affecting ecosystem health and putting a threat on the native population traditional way of living. In the studies here we analyzed the drought impacts in these regions during the 2000s, which vary in nature and outcomes. We addressed some of the key problems in each of the three regions: i) for the southern agriculture, we tackled the problem of predicting soybean yield based on within-season remote sensing (RS) data, ii) in the northeast we mapped areas presenting trends of land degradation in the wake of an extended drought and, iii) in southern Amazon, we characterized a complex degradation cycle encompassing LUC, fire occurrence, forest resilience loss, carbon balance, and the interconnectedness of these factors impacting the local climate. Advisor: Brian D. Wardlo

Vegetation Dynamics Revealed by Remote Sensing and Its Feedback to Regional and Global Climate

This book focuses on some significant progress in vegetation dynamics and their response to climate change revealed by remote sensing data. The development of satellite remote sensing and its derived products offer fantastic opportunities to investigate vegetation changes and their feedback to regional and global climate systems. Special attention is given in the book to vegetation changes and their drivers, the effects of extreme climate events on vegetation, land surface albedo associated with vegetation changes, plant fingerprints, and vegetation dynamics in climate modeling