One pervasive use of the Grindr mobile application is the initiation and accomplishment of pseudonymous sexual encounters between gay strangers based on location awareness. Not only are such encounters oriented towards quasi-immediate sexual gratification, but they are collaboratively done so as to preclude repeat encounters and relational development, with the protagonists supposedly left unaffected emotionally, relationally and socially by their meeting. This creates a rather special – and analytically interesting – interactional dilemma when Grindr users initiate a social contact with potential partners, usually through the chat function integrated into the mobile app. This article describes the way Grindr users have developed a particular ‘linguistic ideology’, which casts ordinary conversation as an interactional activity that is performed between (potential) friends and enables relational development. As such, it is unsuitable for one-time sexual encounters, the production of which is a distinctive and accountable interactional accomplishment. This article analyzes the special interactional practices based on profile-matching sequences which Grindr users have developed to circumvent the relational affordances of electronic conversation. These practices constitute Grindr users as a particular form of speech community, adjusted both to their orientation towards initiating ‘purely’ sexual encounters and to the socio-material design of the Grindr mobile application.

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Accurate estimation of leaf chlorophyll content (Cab) from remote sensing is of tremendous significance to monitor the physiological status of vegetation or to estimate primary production. Many vegetation indices (VIs) have been developed to retrieve Cab at the canopy level from meter-to decameter-scale reflectance observations. However, most of these VIs may be affected by the possible confounding influence of canopy structure. The objective of this study is to develop methods for Cab estimation using millimeter to centimeter spatial resolution reflectance imagery acquired at the field level. Hyperspectral images were acquired over sugar beet canopies from a ground-based platform in the 400-1000 nm range, concurrently to Cab, green fraction (GF), green area index (GAI) ground measurements. The original image spatial resolution was successively degraded from 1 mm to 35 cm, resulting in eleven sets of hyperspectral images. Vegetation and soil pixels were discriminated, and for each spatial resolution, measured Cab values were related to various VIs computed over four sets of reflectance spectra extracted from the images (soil and vegetation pixels, only vegetation pixels, 50% darkest and brightest vegetation pixels). The selected VIs included some classical VIs from the literature as well as optimal combinations of spectral bands, including simple ratio (), modified