Recent advancements in the application of unmanned aerial vehicles (UAVs) based remote
sensing (RS) in precision agricultural practices have been critical in enhancing crop health …

Properties of spatially explicit data are often ignored or inadequately handled in machine
learning for spatial domains of application. At the same time, resources that would identify …

For sustainability and efficiency in maintaining high crop yield and less chemically polluted
agricultural lands, precise weed mapping is essential for the total implementation of site …

As a global problem of soil degradation, salinization has become a major obstacle to the
sustainable development of the ecological environment and agriculture in coastal plains …

Fine classification of wetland vegetation communities using machine learning algorithm and
high spatial resolution images have attracted increased attention. However, there exist …

Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield
loss worldwide. Remote sensing can detect and map the presence of weeds in various …

Introduction Remote sensing using unmanned aerial systems (UAS) are prevalent for
phenomics and precision agricultural applications. The high-resolution data for these …

Prioritization of pathways to perform asphalt pavement operations has always been one of
the most important concerns for municipalities, for which, currently there is no specific …

The sustainable development of agriculture is closely related to the adoption of precision
agriculture techniques, and accurate crop classification is a fundamental aspect of this …

Increasing knowledge in the law of particulate matter (PM) distributions beside elevated
expressways could assist in addressing the deterioration of urban air quality. However, the …