NDVI time series analysis for desert locust outbreak detection and quantification analysis of its impact on vegetation productivity of Sahel

إنجليزي. It has been shown that the semi-arid environment of the Sahelian belt plays an important role in the global carbon uptake as the fluctuation of its primary productivity can be determinant for the global carbon uptake. The insect Schistocerca gregaria commonly known as the desert locust is a disturbance factor that can affect the vegetation productivity for consecutive seasons. In this study the detection of the desert locust outbreaks during the 2003-2005 upsurge was attempted through a Time Series Analysis of seasonal NDVI (small integral) coupled with detailed field observations. In cases of severely infested pixels the seasonal greenness could appear to be lower during the suffering season of 2004 compared to the 14-year interannual average of the pixel examined, indicating that the pixel is infested. At the same time Sahel’s gross primary productivity (GPP) loss due to the locust outbreak was specified by comparing modeled gross primary productivity estimations between the outbreak and the non-outbreak years. The negative impact on primary productivity was also analyzed for the various stages of locust infestations. The process was based on a z-score statistical analysis while the index of Rain Use Efficiency was introduced in order to optimize the method. The outcome of the study showed that the decrease of seasonal NDVI in the infested pixels during the year of the upsurge is not statistically significant and consequently a relationship between greenness and locust infestations cannot be established for the development of a detection tool. Secondly, a significant negative impact on vegetation productivity due to locust outbreaks cannot be confirmed by analyzing the negative divergence from its interannual average. Furthermore, the claim that NDVI and GPP would indicate exceptionally low productivity performance during the year of the upsurge is disproved by the fact that also in years in which the studied pixels were not infested, those measures demonstrate similarly low behavior. The addition of the RUE index was not proven successful as it was shown that the RUE was highly regulated by the fraction’s denominator fluctuation, precipitation. Finally, it has been shown that the negative impact on productivity and seasonal greenness slightly variates between the different stages of infestations. The inadequacy to establish relationship between the field observations and the greenness can be attributed to various factors such as the spatial resolution, the heterogenous nature of vegetation and the field observation selection criteria and treatment.

إنجليزي. The insect Schistocerca gregaria commonly known as the desert locust has been notorious for its destructive impact since it is mentioned as one of the plagues in the Old Testament. Huge numbers of flying insects invade an area and destroy crops causing famine and despair. However, not only crops suffer from locust attacks. All kinds of vegetation get defoliated due to their hunger. Thus, causing a massive impact on the hosting ecosystem by affecting its primary productivity. Primary productivity refers to the ability of a plant to grow, as a result of the photosynthesis process, during which under the effect of solar radiation the inorganic compounds convert into organic ones by using the carbon available in the atmosphere as CO2. Measuring primary productivity allows us to have an insight into how CO2 flows towards the organic part of the ecosystem and to estimate and model the vital carbon cycle. Numerous studies work in this direction, focusing on all parts of the carbon cycle on earth. In the same context, one part of the current study explores the possibility to quantify the productivity decrease due to the desert locust in the large and ecologically important area of the Sahel in Africa. Of equal importance was the exploration of a tool for detecting the locust outbreaks through a satellite-based method. The areas of potential locust spread extend from the western shores of Africa to the west, to the river Indus on the east. In this region, a complete detection of outbreaks is practically impossible by land means. Different types of Satellite images can cover this wide area offering various observation possibilities. This study used a technique based on series of satellite images (Time Series Analysis) focused on greenness, the most characteristic attribute of vegetation, which was measured by the well-known remote sensing vegetation index called Normalized Difference Vegetation Index (NDVI). By monitoring the annual fluctuation of vegetation’s greenness and specifying its average behavior over a relatively long period of time (as long as the data available, in this case 14 years), probable outliers could reveal an abnormal vegetation condition that could reveal the locust presence. In other words, since the locust outbreaks cause severe damage to the leaves (vegetation greenness estimated on the satellite image), their presence could be revealed when greenness estimations are abnormally low. Especially when it is already known that in the area the conditions are favoring the locust migration. In the study this method was tested based on existing field observations of locust outbreaks for which the corresponding NDVI series were examined.