The 2019–2020 Desert Locust (DL) upsurge in East Africa threatened food security for millions in the region. This highlighted the need to track and quantify the damaging impacts of the swarming insects on cropland and rangelands. Satellite Earth observations (EO) data have the potential to contribute to DL damage assessments that can inform control measures, aid distribution and recovery efforts. EO can complement traditional ground based surveys (which are currently further limited due to COVID-19), by rapidly and cost effectively capturing the full spatial scale of the DL upsurge. However, EO-based techniques struggled to accurately quantify damage from this DL upsurge due to the sporadic and localized nature of infestations impacting scale, timing, and anomalous vegetation conditions. This study analyzed time series data from MODIS, the harmonized Landsat Sentinel-2 product, and C-band radar data from Sentinel-1 to distinguish DL damage from normal senescence or other confounding factors from January to June 2020. These data were compared to in situ locust swarm, band, and non locust observations collected by the Food and Agriculture Organization (FAO) and PlantVillage. The methods presented did not produce results that could confidently differentiate senescence from locust activity, and may represent a limitation of publicly available remotely sensed data to detect DL damage. However, the higher spatial resolution data sets showed promise, and there is potential to explore commercially available satellite products such as Planet Labs for damage assessment protocols.

Forest stand height (FSH), or average canopy height, serves as an important indicator for forest monitoring. The information provided about above-ground biomass for greenhouse gas emissions reporting and estimating carbon storage is relevant for reporting for Reducing Emissions from Deforestation and Forest Degradation (REDD+). A novel forest height estimation method utilizing a fusion of backscatter and Interferometric Synthetic Aperture Radar (InSAR) data from JAXA’s Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) is applied to a use case in Savannakhet, Lao. Compared with LiDAR, the estimated height from the fusion method had an RMSE of 4.90 m and an R2 of 0.26. These results are comparable to previous studies using SAR estimation techniques. Despite limitations of data quality and quantity, the Savannakhet, Lao use case demonstrates the applicability of these techniques utilizing L-band SAR data for estimating FSH in tropical forests and can be used as a springboard for use of L-band data from the future NASA-ISRO SAR (NISAR) mission.

No abstract