scholarly journals LAND COVER CLASSIFICATION USING A UAV-BORNE SPECTROMETER

Author(s):  
S. Natesan ◽  
G. Benari ◽  
C. Armenakis ◽  
R. Lee

Small fixed wing and rotor-copter unmanned aerial vehicles (UAV) are being used for low altitude remote sensing for thematic land classification and precision agriculture applications. Various sensors operating in the non-visible spectrum such as multispectral, hyperspectral and thermal sensors can be used as payloads. This work presents a preliminary study on the use of unmanned aerial vehicle equipped with a compact spectrometer for land cover type characterization. When calibrated, the measured spectra by the UAV spectrometer can be processed and compared reference data to generate georeferenced reflection spectra enabling the identification, classification and characterization of land cover elements. For this case study we used a DJI Flamewheel F550 hexacopter and the FLAME-NIR spectrometer for hyperspectral measurements. The calibration of the spectrometer is described as well the approach to determine its spatial footprint. The spectrometer spectral exposure labeled ground point can be used to determine the land cover classification. Preliminary results of a case-study are presented.

Author(s):  
Carmelo Riccardo Fichera ◽  
Giuseppe Modica ◽  
Maurizio Pollino

One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.


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