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Remote sensing satellites are playing very important roles in diverse earth observation fields. However, long revisit period, high cost and dense cloud cover have been the main limitations of satellite remote sensing for a long time. This paper introduces the novel volunteered passenger aircraft remote sensing (VPARS) concept, which can partly overcome these problems. By obtaining aerial imaging data from passengers using a portable smartphone on a passenger aircraft, it has various advantages including low cost, high revisit, dense coverage, and partial anti-cloud, which can well complement conventional remote sensing data. This paper examines the concept of VPARS and give general data processing framework of VPARS. Several cases were given to validate this processing approach. Two preliminary applications on land cover classification and economic activity monitoring validate the applicability of the VPARS data. Furthermore, we examine the issues about data maintenance, potential applications, limitations and challenges. We conclude the VPARS can benefit both scientific and industrial communities who rely on remote sensing data.

Remote sensing satellites are playing very important roles in diverse earth observation fields. However, long revisit period, high cost and dense cloud cover have been the main limitations of satellite remote sensing for a long time. This paper introduces the novel volunteered passenger aircraft remote sensing (VPARS) concept, which can partly overcome these problems. By obtaining aerial imaging data from passengers using a portable smartphone on a passenger aircraft, it has various advantages including low cost, high revisit, dense coverage, and partial anti-cloud, which can well complement conventional remote sensing data. This paper examines the concept of VPARS and give general data processing framework of VPARS. Several cases were given to validate this processing approach. Two preliminary applications on land cover classification and economic activity monitoring validate the applicability of the VPARS data. Furthermore, we examine the issues about data maintenance, potential applications, limitations and challenges. We conclude the VPARS can benefit both scientific and industrial communities who rely on remote sensing data. [ABSTRACT FROM AUTHOR]

Corners are important features in images because they typically delimit the boundaries of regions or objects. For real‐time applications, it is essential that corners are detected and matched reliably and rapidly. This study presents two related descriptors which are compatible with standard corner detectors and able to be computed and matched at video rate: one encodes the entire region within a corner, whereas the other describes only the region within an object. The advantage of encoding only the region within an object is demonstrated. The noise stability of the descriptors is assessed and compared with that of the popular binary robust independent elementary feature (BRIEF) descriptor, and the matching performances of the descriptors are compared on video sequences from hand‐held cameras and the PETS2012 database. A statistical analysis shows that performance is indistinguishable from BRIEF.