Presentation + Paper
4 October 2017 Semi-autonomous remote sensing time series generation tool
Dinesh Kumar Babu, Christof Kaufmann, Marco Schmidt, Thorsten Dahms, Christopher Conrad
Author Affiliations +
Abstract
High spatial and temporal resolution data is vital for crop monitoring and phenology change detection. Due to the lack of satellite architecture and frequent cloud cover issues, availability of daily high spatial data is still far from reality. Remote sensing time series generation of high spatial and temporal data by data fusion seems to be a practical alternative. However, it is not an easy process, since it involves multiple steps and also requires multiple tools. In this paper, a framework of Geo Information System (GIS) based tool is presented for semi-autonomous time series generation. This tool will eliminate the difficulties by automating all the steps and enable the users to generate synthetic time series data with ease. Firstly, all the steps required for the time series generation process are identified and grouped into blocks based on their functionalities. Later two main frameworks are created, one to perform all the pre-processing steps on various satellite data and the other one to perform data fusion to generate time series. The two frameworks can be used individually to perform specific tasks or they could be combined to perform both the processes in one go. This tool can handle most of the known geo data formats currently available which makes it a generic tool for time series generation of various remote sensing satellite data. This tool is developed as a common platform with good interface which provides lot of functionalities to enable further development of more remote sensing applications. A detailed description on the capabilities and the advantages of the frameworks are given in this paper.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dinesh Kumar Babu, Christof Kaufmann, Marco Schmidt, Thorsten Dahms, and Christopher Conrad "Semi-autonomous remote sensing time series generation tool", Proc. SPIE 10427, Image and Signal Processing for Remote Sensing XXIII, 104270C (4 October 2017); https://doi.org/10.1117/12.2278213
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KEYWORDS
Remote sensing

Data fusion

Satellites

Data processing

Ecology

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