Remote sensing technologies have been commonly used to perform greenhouse detection and mapping. In this research, stereo pairs acquired by very high-resolution optical satellites GeoEye-1 (GE1) and WorldView-2 (WV2) have been utilized to carry out the land cover classification of an agricultural area through an object-based image analysis approach, paying special attention to greenhouses extraction. The main novelty of this work lies in the joint use of single-source stereo-photogrammetrically derived heights and multispectral information from both panchromatic and pan-sharpened orthoimages. The main features tested in this research can be grouped into different categories, such as basic spectral information, elevation data (normalized digital surface model; nDSM), band indexes and ratios, texture and shape geometry. Furthermore, spectral information was based on both single orthoimages and multiangle orthoimages. The overall accuracy attained by applying nearest neighbor and support vector machine classifiers to the four multispectral bands of GE1 were very similar to those computed from WV2, for either four or eight multispectral bands. Height data, in the form of nDSM, were the most important feature for greenhouse classification. The best overall accuracy values were close to 90%, and they were not improved by using multiangle orthoimages.
The use of archival or historical photography for photogrammetric purposes often involves a lack of data concerning the aerial cameras employed, difficulties in identifying control points on the photos and inappropriate conservation of the photography. When camera calibration parameters are unknown, they should be estimated by means of a self‐calibrating bundle adjustment. Several calibration models available in the Leica Photogrammetry Suite software have been tested on two archival datasets, captured in 1956 and 1977, covering the same working area. The accuracy of the dataset triangulation was found to depend significantly on the self‐calibration method and the number of ground control points used; when the latter ranged from six to nine per stereopair, self‐calibrating bundle adjustment techniques were found to slightly, but not always significantly, improve the photogrammetric capability of archival aerial photography. Thus, the adoption of self‐calibration cannot guarantee the improvement of results when working on poorly conserved imagery. Results from such datasets are very dependent on numerous local variables which cannot be extrapolated to other areas for the same camera since each dataset is unique and may present systematic errors of a different nature.
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