The use of miniaturized satellites for time-series research /
Satellite imagery has been used in academic research since the advent of the NASA Landsat Program in the 1970s. The success of that program and continuous advances in technology have led to increasingly more sophisticated satellites and imaging capabilities while at the same time reducing their size...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
London :
SAGE Publications Ltd,
2024.
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| Series: | SAGE research methods. Cases
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | Satellite imagery has been used in academic research since the advent of the NASA Landsat Program in the 1970s. The success of that program and continuous advances in technology have led to increasingly more sophisticated satellites and imaging capabilities while at the same time reducing their size. Today there are a multitude of satellites with a range of different sensors and capabilities, but one type that has become increasingly popular is the miniaturized satellite, or so-called CubeSats. These miniaturized satellites are constellations of tiny satellites that allow for the capture of high-resolution images of the Earth's surface daily and at a much lower cost for end users. Here we demonstrate use of the CubeSats constellation PlanetScope to estimate the area extent of an endangered ecosystem, the Central Pine Barrens, using a combination of remote-sensing time-series data and machine-learning modeling. we also highlight the tradeoffs, limitations, and considerations of using these types of data sets and methods. Overall, my results indicate the potential of combining CubeSats, time-series data, and machine learning, with an overall accuracy of 93% and a Cohen's kappa of 0.853. |
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| Physical Description: | 1 online resource. |
| ISBN: | 9781529681550 1529681553 |