A Linear Regression Approach for Best Scanline Determination in the Object to Image Space Transformation Using Pushbroom Images.

The use of linear array pushbroom images presents a new challenge in photogrammetric applications when it comes to transforming object coordinates to image coordinates. To address this issue, the Best Scanline Search/Determination (BSS/BSD) field focuses on obtaining the Exterior Orientation Parameters (EOPs) of each individual scanline. Current solutions are often impractical for real-time tasks due to their high time requirements and complexities.

Predicting the environmental suitability for Anopheles stephensi under the current conditions in Ghana.

Vector-borne diseases emergence, particularly malaria, present a significant public health challenge worldwide. Anophelines are predominant malaria vectors, with varied distribution, and influenced by environment and climate. This study, in Ghana, modelled environmental suitability for Anopheles stephensi, a potential vector that may threaten advances in malaria and vector control.

Predicting current and future high-risk areas for vectors and reservoirs of cutaneous leishmaniasis in Iran.

Climate change will affect the distribution of species in the future. To determine the vulnerable areas relating to CL in Iran, we applied two models, MaxEnt and RF, for the projection of the future distribution of the main vectors and reservoirs of CL. The results of the models were compared in terms of performance, species distribution maps, and the gain, loss, and stable areas.

Temporal Monitoring and Predicting of the Abundance of Malaria Vectors Using Time Series Analysis of Remote Sensing Data through Google Earth Engine.

In many studies regarding the field of malaria, environmental factors have been acquired in single-time, multi-time or a short-time series using remote sensing and meteorological data. Selecting the best periods of the year to monitor the habitats of larvae can be effective in better and faster control of malaria outbreaks. In this article, high-risk times for three regions in Iran, including Qaleh-Ganj, Sarbaz and Bashagard counties with a history of malaria prevalence were estimated.