Effect of Locust Invasion and Mitigation Using Remote Sensing Techniques: A Case Study of North Sindh Pakistan

Abstract

This study comprises the identification of the locust outbreak that happened in February 2020. It is not possible to conduct ground-based surveys to monitor such huge disasters in a timely and adequate manner. Therefore, we used a combination of automatic and manual remote sensing data processing techniques to find out the aftereffects of locust attack effectively. We processed MODIS -normalized difference vegetation index (NDVI ) manually on ENVI and Landsat 8 NDVI using the Google Earth Engine (GEE ) cloud computing platform. We found from the results that, (a) NDVI computation on GEE is more effective, prompt, and reliable compared with the results of manual NDVI computations; (b) there is a high effect of locust disasters in the northern part of Sindh, Thul, Ghari Khairo, Garhi Yaseen, Jacobabad, and Ubauro, which are more vulnerable; and (c) NDVI value suddenly decreased to 0.68 from 0.92 in 2020 using Landsat NDVI and from 0.81 to 0.65 using MODIS satellite imagery. Results clearly indicate an abrupt decrease in vegetation in 2020 due to a locust disaster. That is a big threat to crop yield and food production because it provides a major portion of food chain and gross domestic product for Sindh, Pakistan.