Abstract

Volcanic eruptions cause pyroclastic flows, which can destroy plantations and settlements. We used image data from Landsat 7 Bands 7, 4 and 2 and Landsat 8 Bands 7, 5 and 3 to observe and analyze the distribution of pyroclastic flow deposits for two volcanos, Mount Sinabung and Merapi, over a period of 10 years (2001–2017). The satellite data are used in conjunction with an artificial neural network method to produce maps of pyroclastic precipitation for Landsat 7 and 8, then we calculated the pyroclastic precipitation area using an artificial neural network method after dividing the images into four classes based on color. Red, green, blue and yellow were used to indicate pyroclastic deposits, vegetation and forest, water and cloud, and farmland, respectively. The area affected by a volcanic eruption was deduced from the neural network processing, including calculating the area of pyroclastic deposits. The main differences between the pyroclastic flow deposits of Mount Sinabung and Mount Merapi are: the sediment deposits of the pyroclastic flows of Mount Sinabung tend to widen, whereas those of Merapi elongated; the direction of pyroclastic flow differed; and the area affected by an eruption was greater for Mount Merapi than Mount Sinabung because the VEI (Volcanic Explosivity Index) during the last 10 years of Mount Merapi was larger than Mount Sinabung.

Highlights

  • Remote sensing research has used multispectral remote sensing imagery to provide additional data, proving to be a valuable source of spatio-temporal data for some applications

  • Appropriate knowledge, updated and temporal, about Land cover assessment (LC) is very important to address the issue of unplanned development, environmental degradation, loss of wildlife habitat and depletion of primary agricultural and forest land [4]

  • It is important to evaluate and monitor the LC dynamics resulting from anthropogenic activities and natural phenomena to plan, monitor and sustain the utilization of natural resources [5]

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Summary

Introduction

Remote sensing research has used multispectral remote sensing imagery to provide additional data, proving to be a valuable source of spatio-temporal data for some applications. Land cover assessment (LC) is very important in planning, monitoring and sustaining the utilization of natural resources. LC has a direct impact on water, atmospheric and soil erosion and is directly related to many globally-important environmental issues [3]. Appropriate knowledge, updated and temporal, about LC is very important to address the issue of unplanned development, environmental degradation, loss of wildlife habitat and depletion of primary agricultural and forest land [4]. It is important to evaluate and monitor the LC dynamics resulting from anthropogenic activities and natural phenomena to plan, monitor and sustain the utilization of natural resources [5]

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