|
|
|
Yujuan Cao, Jianguo Dai, Guoshun Zhang, Minghui Xia and Zhitan Jiang
This paper combines feature selection with machine learning algorithms to achieve object-oriented classification of crops in Gaofen-6 remote sensing images. The study provides technical support and methodological references for research on regional monit...
ver más
|
|
|
|
|
|
|
Vasileios Moysiadis, Ilias Siniosoglou, Georgios Kokkonis, Vasileios Argyriou, Thomas Lagkas, Sotirios K. Goudos and Panagiotis Sarigiannidis
Remote sensing stands out as one of the most widely used operations in the field. In this research area, UAVs offer full coverage of large cultivation areas in a few minutes and provide orthomosaic images with valuable information based on multispectral ...
ver más
|
|
|
|
|
|
|
Hui Deng, Wenjiang Zhang, Xiaoqian Zheng and Houxi Zhang
The accurate and timely identification of crops holds paramount significance for effective crop management and yield estimation. Unmanned aerial vehicle (UAV), with their superior spatial and temporal resolution compared to satellite-based remote sensing...
ver más
|
|
|
|
|
|
|
Shihao Ma, Jiao Wu, Zhijun Zhang and Yala Tong
Addressing the limitations, including low automation, slow recognition speed, and limited universality, of current mudslide disaster detection techniques in remote sensing imagery, this study employs deep learning methods for enhanced mudslide disaster d...
ver más
|
|
|
|
|
|
|
Ziwei Tian, Jie Huang, Yang Yang and Weiying Nie
Aerial remote sensing image object detection, based on deep learning, is of great significance in geological resource exploration, urban traffic management, and military strategic information. To improve intractable problems in aerial remote sensing imag...
ver más
|
|
|
|
|
|
|
Zhu Zhu, Tinggang Zhou, Jinsong Chen, Xiaoli Li, Shanxin Guo, Longlong Zhao and Luyi Sun
Change detection for remote sensing images.
|
|
|
|
|
|
|
Ahram Song
Deep learning techniques have recently shown remarkable efficacy in the semantic segmentation of natural and remote sensing (RS) images. However, these techniques heavily rely on the size of the training data, and obtaining large RS imagery datasets is d...
ver más
|
|
|
|
|
|
|
Hui Li, Xueshan Bai, Xing Zhai, Jianqing Zhao, Xiaolong Zhu, Chenxi Li, Kehui Liu and Qizhi Wang
Mountain mudslides have emerged as one of the main geological dangers in the Yanshan region of China as a result of excessive rains. In light of this, a multi-step debris flow hazard assessment method combining optimal weights and a topological object me...
ver más
|
|
|
|
|
|
|
Wenjie Guo, Ayong Jiao, Wenqi Wang, Chaoqun Chen, Hongbo Ling, Junjie Yan and Fulong Chen
In arid regions with scarce water resources, lakes play an extremely vital role in maintaining the ecological environment. Therefore, the Chinese government has launched an ecological water conveyance project in the Tarim River basin in Xinjiang with the...
ver más
|
|
|
|
|
|
|
Jianjun Chen, Zizhen Chen, Renjie Huang, Haotian You, Xiaowen Han, Tao Yue and Guoqing Zhou
When employing remote sensing images, it is challenging to classify vegetation species and ground objects due to the abundance of wetland vegetation species and the high fragmentation of ground objects. Remote sensing images are classified primarily acco...
ver más
|
|
|
|