论文信息 - Deep convolutional neural network based large-scale oil palm tree detection for high-resolution remote sensing images

Deep convolutional neural network based large-scale oil palm tree detection for high-resolution remote sensing images

This paper proposed a deep convolutional neural network (DCNN) based framework for large-scale oil palm tree detection using high-resolution remote sensing images in Malaysia. Different from the previous palm tree or tree crown detection studies, the palm trees in our study area are very crowded and their crowns often overlap. Moreover, there are various land cover types in our study area, e.g. impervious, bare land, and other vegetation, etc. The main steps of our proposed method include large-scale and multi-class sample collection, AlexNet-based DCNN training and optimization, sliding window-based label prediction, and post-processing. Compared with the manually interpreted ground truth, our proposed method achieves detection accuracies of 92%–97% in our study area, which are greatly higher than the accuracies obtained from another two detection methods used in this paper.

Weijia Li | Le Yu | Haohuan Fu

[1] Congcong Li,et al. Stacked Autoencoder-based deep learning for remote-sensing image classification: a case study of African land-cover mapping , 2016 .

[2] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[3] Yinghai Ke,et al. A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing , 2011 .

[4] Wei Wang,et al. CNN based suburban building detection using monocular high resolution Google Earth images , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[5] Shiming Xiang,et al. Vehicle Detection in Satellite Images by Hybrid Deep Convolutional Neural Networks , 2014, IEEE Geoscience and Remote Sensing Letters.

[6] P. Gong,et al. Oil palm mapping using Landsat and PALSAR: a case study in Malaysia , 2016 .

[7] Weijia Li,et al. Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images , 2016, Remote. Sens..

[8] Douglas J. King,et al. Automated tree crown detection and delineation in high-resolution digital camera imagery of coniferous forest regeneration , 2002 .

[9] Tong Zhang,et al. Deep Learning Based Feature Selection for Remote Sensing Scene Classification , 2015, IEEE Geoscience and Remote Sensing Letters.