Change detection techniques for remote sensing applications: a survey

By Anju Asokan, J. Anitha. Earth Science Informatics, 2019

358 citations recorded by the source corpus.

Subfields: Atmospheric Science, Ecology, Media Technology

View Paper: https://www.semanticscholar.org/paper/90f376d7e23e53133a472ea74bcaeeac8ac08586

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Xiaoping Liu
2. Fei Wang
3. Mengxi Liu
4. Shengchen Li
5. Qian Shi
6. Liangpei Zhang
7. Bo Du

In Ecology

1. Xiaoping Liu
2. Fei Wang
3. Mengxi Liu
4. Shengchen Li
5. Qian Shi
6. Liangpei Zhang

In Media Technology

1. Xiaoping Liu
2. Fei Wang
3. Mengxi Liu
4. Shengchen Li
5. Qian Shi
6. Liangpei Zhang
7. Bo Du
8. Xiaoqiang Lu

Citations in the corpus

• A Deeply Supervised Attention Metric-Based Network and an Open Aerial Image Dataset for Remote Sensing Change Detection (2021, background): “Meanwhile, high-resolution multisource and multitemporal remote sensing images can be obtained over different areas, which have been proven to be a key source of primary data for change detection (CD) because of their wide coverage, high temporal resolution, and diverse data types [6].”