# An Overview of Infrared Remote Sensing of Volcanic Activity
## 5 Infrared Remote Sensing of Volcanoes: A History  
Given the previous detail concerning the infrared sensors used for monitoring volcanic activity, it will be evident that the discipline has a history of over half a century. As technology has progressed, so have the applications to which the discipline has been applied [81], and these will be highlighted here. Early infrared radiometer remote sensing surveys were airborne, as opposed to in Earth orbit, with [82] describing this application to Hawaiian volcanoes and producing more detailed and accurate thermal maps than had been possible from land-based observations alone. Later, [83; 84] presented radiance maps and detailed how thermal emissions varied spatially at the new Icelandic volcanic islands of Surtsey and Jolnir. [PERSON] and [PERSON] [85; 86] also describe aerial volcanic surveys in Italy and at Mount St. Helens, respectively. [PERSON] et al. [87] was the first study to use satellite-acquired infrared data in the detection and monitoring of volcanic activity. However, despite such early experimental endeavours, it remains the case that even today, no satellite sensor has been launched with the sole aim of volcanic infrared monitoring. Volcanoists have been inventive and made use of sensors launched for purposes other than volcanic observation, and unfortunately, nothing seems set to alter this requirement in the near future. [PERSON] et al. [39] stated, in relation to volcanic remote sensing, that \"infrared remote-sensing methods remain of limited use\" (p. 293), and at the time, this will have done little to encourage take-up of the discipline. This assessment was set to change however, as the discipline soon began to burgeon. [PERSON] and [PERSON] [88; 89] showed how thermal activity at remote Andean volcanoes could be identified without the need for costly and dangerous fieldwork, while [90] took a more global approach, highlighting the general utility of satellite infrared monitoring of volcanoes. Qualitative studies gradually became quantitative, with [91], for example, becoming the first study to consider volcanic surface power emissions as opposed to values of radiance. [PERSON] [81; 36] provides detailed chronologies of the development of the discipline that cannot be bettered here, but in summary, it is shown that during the 1990s, the discipline expanded significantly. The work of [PERSON] et al. [32] is perhaps responsible for stimulating most interest, by promoting the volcanic utility of the forthcoming NASA Earth Observation System. The initial priority during this period, according to [81], was the identification of 'hotspots' and following this, the isolation of temperature distributions (e.g., [45; 92; 93]). Once perfected in their observations, such studies became more quantitative in their focus and increasingly attempted to relate remote observations to actual phenomena on the ground. [PERSON] et al. [31; 92], for example, were able to identify eruptive periods from a time series of satellite data for Lascar Volcano, Chile, while [42; 94] showed how infrared observations could be used to estimate lava effusion rates. It was slowly becoming evident that a reliable and direct relationship existed between the radiant heat emitted from a volcano and the type and intensity of activity displayed at the surface. During this period, the potential seen in the discipline was highlighted in a review paper entitled: 'Remote Sensing of Active Volcanoes' [24]. With the small volumes of data coming from the handful of early infrared remote sensors, the early process of detecting the thermal signatures of volcanic activity was largely manual, but between 1995 and 2010, many automated algorithms were developed to detect volcanic thermal anomalies and to avoid false-alarms [81]. [PERSON] et al. [95], for example, developed an algorithm for AVHRR MIR observations, which identified hotspots within a uniformly warm surface, by harnessing the radiance temperature difference between Bands 3 (3.8 \(\upmu\)m) and 4 (10.8 \(\upmu\)m).