全球情况不断变化的情形下，土地使用/土地覆盖动态变化评估对评价全球和区域生态系统的变化至关重要。
大规模城市土地覆被分类是遥感领域的经典课题，它引导着城市基础设施规划、产业布局、资源管理等，是政策制定者的重点关注内容之一。
基于深度CNN的LULC谱分类器原理图
随着深度学习技术的发展，各头部科技公司与互联网企业也越来越重视城市模型的建设与投入，将新技术与算法引入到这一经典研究课题中。
这次我整理了18篇遥感经典论文，希望对大家的学习有所启发。
扫描二维码，回复【遥感】
领取文中18篇经典遥感论文
全是pdf格式，非常方便，想要的同学千万不要错过！
1、Deep learning in environmental remote sensing: Achievements and challenges
2、ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci
3、Review on remote sensing methods for landslide detection using machine and deep learning
4、Deep Learning for Medicine and Remote Sensing: A Brief Review
5、Deep learning in remote sensing applications: A meta-analysis and review
6、Deep learning classifiers for hyperspectral imaging: A review
7、Deep Learning for Classification of Hyperspectral Data: A Comparative Review
8、Deep neural network for remote sensing image interpretation: status and perspectives
9、Deep Learning for Hyperspectral Image Classification: An Overview
10、A Review of Researches on Deep Learning in Remote Sensing Application
11、Implementation of machine-learning classification in remote sensing: an applied review
12、Deep learning for remote sensing image classification: A survey
13、
Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources
14、Remote Sensing Image Scene Classification: Benchmark and State of the Art. Proceedings of the IEEE
15、Deep learning for urban remote sensing
16、Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community
17、Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art
18、Deep Learning for Remote Sensing Image Understanding.
扫描二维码，回复【遥感】
领取文中18篇经典遥感论文
全是pdf格式，非常方便，想要的同学千万不要错过！
