¶ Forestry digital twin using Landsat 7
Description: Modeling forests using historical data allows for more accurately evolution analysis, thus
providing an important basis for other studies. As a recognized and effective tool, remote sensing
plays an important role in forestry analysis. We can use it to derive information about the forest,
including tree type, coverage and canopy density. There are many forest time series modeling
studies using statistic values, but few using remote sensing images. Image prediction digital twin
is an implementation of digital twin, which aims to predict future images bases on historical data.
In this paper, we propose an LSTM-based digital twin approach for forest modeling, using Landsat
7 remote sensing image within 20 years. The experimental results show that the prediction twin
method in this paper can effectively predict the future images of study area.
Category: Remote Sensing, Imaging & Analytics
FWPA RD&E: 7.3
¶ Details
| Company | Country | Type | Website | Available in Australia? | Year | Status | Remarks | TRL | Employees | Colour | Inventors | Patent Model. |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Jiang et al. | Cornell University | Paper | Link | 2022 | Red |