This paper presents a statistical method for deriving optimal spatial sampling schemes. It focuses on ground verification of minerals derived from hyperspectral data. Spectral angle mapper (SAM) and spectral feature fitting (SFF) classification techniques were applied to obtain rule mineral images. The rule images provide weights that are utilized in simulated annealing. A HyMAP 126channel airb...

It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79 to 24.85 in latitude and 66.91 to 66.97 in longitude using hyperspectral remote sensing data and techniques. Image a...

A few dominant tree species in temperate forests of western Himalayas have been mapped using Hyperion data. The data was processed for removing atmospheric distortions using FLAASH before classification. The replicate spectral profiles were collected in ground using field spectrometer (ASD) during same season for classification. Reconnaissance survey was conducted to locate populations or suffi...

A hyperspectral image can be considered as an image cube where the third dimension is the spectral domain represented by hundreds of spectral wavelengths. As a result, a hyperspectral image pixel is actually a column vector with dimension equal to the number of spectral bands and contains valuable spectral information that can be used to account for pixel variability, similarity, and discrimina...

The development of advanced laboratory-based imaging hyperspectral sensors, such as SisuCHEMA, has created an opportunity to extract compositional information of mineral mixtures from spectral images. Determining proportions of minerals on rock surfaces based on spectral signature is a challenging approach due to naturally-occurring minerals that exist in the form of intimate mixtures, and grai...

Intertidal macroalgal habitats are major components of temperate coastal ecosystems. Their distribution was studied using field sampling and hyperspectral remote mapping on a rocky shore Porspoder (western Brittany, France). Covers both dominating macroalgae the sessile fauna were characterized in situ at low tide 24 spots, according to four bathymetric levels. A zone ca. 17,000 m2 drone equipp...

The reflectance spectrum of the species in a hyperspectral data can be modelled as an n­dimensional vector. The spectral angle mapper computes the angle between the vectors which is used to discriminate the species. The spectral information divergence models the data as a probability distribution so that the spectral variability between the bands can be extracted using the stochastic measures. ...

Visual image interpretation and digital image classification have been used to map and monitor mangrove extent and composition for decades. The presence of a high-spatial resolution hyperspectral sensor can potentially improve our ability to differentiate mangrove species. However, little research has explored the use of pixel-based and object-based approaches on high-spatial hyperspectral data...

A passive method for remote sensing of the nuisance green algae Cladophora glomerata in rivers is presented using an unmanned aerial vehicle (UAV). Included are methods for UAV operation, lens distortion correction, image georeferencing, and spectral analysis to support algal cover mapping. Eighteen aerial photography missions were conducted over the summer of 2013 using an off-the-shelf UAV an...

Urban land cover classification using remote sensing data is quite challenging due to spectrally and spatially complex urban features. The present study describes the potential use of hyperspectral data for urban land cover classification and its comparison with multispectral data. EO-1 Hyperion data of October 05, 2012 covering parts of Bengaluru city was analyzed for land cover classification...