Using satellite imagery for African bird conservation

Dust source mapping using satellite imagery and machine learning models

Predicting dust sources area and determining the affecting factors is necessary in order to prioritize management and practice deal with desertification due to wind erosion in arid areas. Therefore, this study aimed to evaluate the application of three machine learning models (including generalized linear model, artificial neural network, random forest) to predict the vulnerability of dust cent...

Validation of Volunteered Geographic Information Landuse Change Using Satellite Imagery

Land use change monitoring is one of the main concerns of managers and urban planners due to human activities and unbalanced physical development in urban areas. In this paper, a combination of remote sensing data and volunteered geographic information was used to assess the quality of volunteered geographic information on land use and land cover changes monitoring. For this purpose, the ORBVIE...

Improved classification of conservation tillage adoption using high temporal and synthetic satellite imagery

Global-scale Object Detection Using Satellite Imagery

In recent years, there has been a substantial increase in the availability of high-resolution commercial satellite imagery, enabling a variety of new remote-sensing applications. One of the main challenges for these applications is the accurate and efficient extraction of semantic information from satellite imagery. In this work, we investigate an important instance of this class of challenges ...

Regional Population Estimation Using Satellite Imagery

Population data provides statistical information that can in turn support decision making processes. It provides essential information regarding many practices such as rescue operations or humanitarian actions, which require the estimation of local population. While traditional approaches are possible, they tend to be time consuming and expensive. Copernicus Earth Observation data (Sentinel 2 s...