This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quali...

Optical imagery such as high-resolution panchromatic or multispectral data, and SAR/INSAR data show different information about the imaged objects, and have different advantages and disadvantages when used for object extraction or landuse classification. Multispectral optical image data is largely determined by the type of the material an object consists of. Panchromatic data which is often ava...

Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use...

There is an increasing interest in the use of high-resolution multispectral data (acquired by small format digital air-borne imaging sensors) for large-scale vegetation mapping. Recent studies have focused on the potential of air-borne multispectral data as a means of identifying plant communities. This study is concerned with establishing a formal relationship between spatial resolution and la...

In remote, rugged or sensitive environments ground based mapping for condition assessment of species is both time consuming and potentially destructive. The application of photogrammetric methods to generate multispectral imagery and surface models based on UAV imagery at appropriate temporal and spatial resolutions is described. This paper describes a novel method to combine processing of NIR ...

This paper presents an improved Artificial Immune System (AIS) approach for unsupervised classification in multispectral remote-sensing imagery. For benchmarking, one has considered several unsupervised nature-inspired intelligent classifiers (AIS, neural, fuzzy) versus statistical ones. We have comparatively evaluated the following pattern recognition techniques: the proposed AIS model; Self-O...

In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and mu...