The distributed networks for information collection of chemical components with high-mobility objects, such as drones or smartphones, will work effectively for investigations, clarifications and predictions against unexpected local terrorisms and disasters like localized torrential downpours. We proposed and reported the proposed spectroscopic line-imager for smartphones in this conference. In this paper, we will mention the wide-area spectroscopic-image construction by estimating 6 DOF (Degrees Of Freedom: parallel movements=x,y,z and rotational movements=θx, θy, θz) from line data to observe and analyze surrounding chemical-environments. Recently, smartphone movies, what were photographed by peoples happened to be there, had worked effectively to analyze what kinds of phenomenon had happened around there. But when a gas tank suddenly blew up, we did not recognize from visible-light RGB-color cameras what kinds of chemical gas components were polluting surrounding atmospheres. Conventionally Fourier spectroscopy had been well known as chemical components analysis in laboratory usages. But volatile gases should be analyzed promptly at accident sites. And because the humidity absorption in near and middle infrared lights has very high sensitivity, we will be able to detect humidity in the sky from wide field spectroscopic image. And also recently, 6-DOF sensors are easily utilized for estimation of position and attitude for UAV (Unmanned Air Vehicle) or smartphone. But for observing long-distance views, accuracies of angle measurements were not sufficient to merge line data because of leverage theory. Thus, by searching corresponding pixels between line spectroscopic images, we are trying to estimate 6-DOF in high accuracy.