High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery

Abstract

Interest in larval source management (LSM) as an adjunct intervention to control and eliminate malaria transmission has recently increased mainly because long-lasting insecticidal nets (LLINs) and indoor residual spray (IRS) are ineffective against exophagic and exophilic mosquitoes. In Amazonian Peru, the identification of the most productive, positive water bodies would increase the impact of targeted mosquito control on aquatic life stages. The present study explores the use of unmanned aerial vehicles (drones) for identifying Nyssorhynchus darlingi (formerly Anopheles darlingi) breeding sites with high-resolution imagery (~0.02m/pixel) and their multispectral profile in Amazonian Peru. Our results show that high-resolution multispectral imagery can discriminate a profile of water bodies where Ny. darlingi is most likely to breed (overall accuracy 86.73%- 96.98%) with a moderate differentiation of spectral bands. This work provides proof-of-concept of the use of high-resolution images to detect malaria vector breeding sites in Amazonian Peru and such innovative methodology could be crucial for LSM malaria integrated interventions.

Open-Source 3D Printable GPS Tracker to Characterize the Role of Human Population Movement on Malaria Epidemiology in River Networks: A Proof-of-Concept Study in the Peruvian Amazon

“…The landscape is composed by dense primary and secondary tropical forest, with a rainy season between November and May, and a dry season between June and October. This ecological setting is highly suitable for Nyssorhynchus (Anopheles) darling breeding, the primary vector of malaria in this area (7,26).…”

Using 1st Derivative Reflectance Signatures within a Remote Sensing Framework to Identify Macroalgae in Marine Environments

“…Other factors such as organic and inorganic matter in the water column, phytoplankton presence, and surface water spectral scattering can cause further detection difficulties. For these reasons, it is likely that the remote sensing of MABs will require a high-resolution remote sensing system such as the centimeter spatial resolution imaging systems used by [69,70].…”

“…A regional-scale early-warning system using UAVs can provide solutions to the temporal, and atmospheric, challenges that satellite systems currently face. There are significant advances being made in UAV mountable sensor types [88,89] and are part of a rapidly advancing field of research [69,90,91]. Different sensor types can be tuned to specific parts of the spectrum using filters [92]; this is particularly common with charge-coupled devices (CCD) and CMOS sensors.…”

The application of drones for mosquito larval habitat identification in rural environments: a practical approach for malaria control?

“…Geospatial technology is rapidly evolving and what now constitutes as 'findable' may switch from less reliance on exhaustive ground-based searches to remotely sensed data. Drone mapping is being touted as at least equivalent (if not superior) to and more cost-effective than mapping larval habitat manually (Carrasco-Escobar et al, 2019;Hardy, Makame, Cross, Majambere, & Msellem, 2017) or using remotely sensed satellite imagery. While the latter can cover vast areas in a single day, images 6 are often obscured by clouds and although very high-resolution commercial satellite imagery exists, the resolution (at best 30 cm) is still inferior to that obtained by drones (2-10 cm) with the time of image captured out of the data user's control.…”