System for automated environmental monitoring using remote sensing data of the Earth from open data sources

K A Maslov,O S Tokareva

doi:10.1088/1757-899x/1019/1/012100

Abstract

Environmental monitoring using remote sensing data requires an analyst to perform a large amount of routine work related to downloading, processing and analyzing data, especially in cases when the study area is covered with a large number of satellite imagery. The paper presents the results of the design and software implementation of the system that automates downloading and processing of remotely sensed data according to developed scenarios and, thus, greatly simplifies the processing of satellite imagery. It provides the description of tools for accessing data from the archive of the United States Geological Survey (USGS) and describes the data flow in the system. The paper gives an analysis of results obtained using the developed system on the example of monitoring the state of Siberian pine forests of the Tomsk region.

Highlights

Monitoring of land cover change using remotely sensed data helps to make an objective assessment of the state of environmental objects and to identify changes occurring because of natural processes or anthropogenic impact
This section gives the description of the results obtained with the SiberianPineForestsScenario scenario for monitoring of the state of the Siberian pine forests of the Tomsk Region, which are specially protected natural areas (Aksenovskiy, Belousovskiy, Bogashevskiy, Loskutovskiy, Luchanovo-Ipatovskiy, Magadaevskiy, Nizhne-Sechenovskiy, Petrovskiy, Petukhovskiy, Plotnikovskiy, Protopopovskiy, Trubachevskiy, Voronovskiy Siberian pine forests and forest park near the village Yar)
The mean values of the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) indices were calculated within the boundaries of the Siberian pine forests of the Tomsk region

Summary

Introduction

Monitoring of land cover change using remotely sensed data helps to make an objective assessment of the state of environmental objects and to identify changes occurring because of natural processes or anthropogenic impact. To solve the problems of monitoring of land-cover change, index images based on combination of pixel values from different electromagnetic spectrum regions are widely used [6,7,8]. Examples of such index images are vegetation index maps, e.g. normalized difference vegetation index (NDVI) or normalized difference water index (NDWI), standing for the amount of photosynthetically active phytomass and water content in leaves and needles of vegetation, respectively [9, 10]. To provide continuous monitoring of the land cover using remotely sensed data of the Earth, it is necessary to have a system that simultaneously automates both the processes of downloading data from external sources and processing of the fetched data according to specific scenarios

System design

19: END WHILE

Results

Conclusion