Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformer-based architectures, originally introduced in natural language processing, have pervaded com...
In recent years, unmanned aerial vehicles (UAVs) have gained popularity due to their flexibility, mobility, and accessibility in various fields, including search and rescue (SAR) operations. The use of UAVs in SAR can greatly enhance the task success...
Because of the recent advances in drones or Unmanned Aerial Vehicle (UAV) platforms, sensors and software, UAVs have gained popularity among precision agriculture researchers and stakeholders for estimating traits such as crop yield and diseases. Ear...
This study provides a comprehensive review of the efforts utilized in the measurement of water quality parameters (WQPs) with a focus on total dissolved solids (TDS) and total suspended solids (TSS). The current method used in the measurement of TDS...
The key elements that underpin food security require the adaptation of agricultural systems to support productivity increases while minimizing inputs and the adverse effects of climate change. The advances in precision agriculture over the past few y...
Weeds are a crucial threat to agriculture, and in order to preserve crop productivity, spreading agrochemicals is a common practice with a potential negative impact on the environment. Methods that can support intelligent application are needed. Ther...
Given the large volume of remote sensing images collected daily, automatic object detection and segmentation have been a consistent need in Earth observation (EO). However, objects of interest vary in shape, size, appearance, and reflecting propertie...
This study provides an overview of the techniques, shortcomings, and strengths of remote sensing (RS) applications in the effective retrieval and monitoring of water quality parameters (WQPs) such as chlorophyll-a concentration, turbidity, total susp...
Reliable and timely crop-yield prediction and crop mapping are crucial for food security and decision making in the food industry and in agro-environmental management. The global coverage, rich spectral and spatial information and repetitive nature o...
Recently, deep learning techniques have been extensively used to detect ships in synthetic aperture radar (SAR) images. The majority of modern algorithms can achieve successful ship detection outcomes when working with multiple-scale ships on a large...
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