一种深度卷积神经网络土地利用场景照片的分类方法

doi:10.13474/j.cnki.11-2246.2020.0039

测绘通报 ›› 2020, Vol. 0 ›› Issue (2): 24-28,42.doi: 10.13474/j.cnki.11-2246.2020.0039

一种深度卷积神经网络土地利用场景照片的分类方法

徐世武¹, 曾珏², 张诗慧¹, 李长征¹, 李亭谕¹

1. 中国地质大学(武汉), 湖北武汉 430074;
2. 中国国土勘测规划院, 北京 100035

收稿日期:2019-11-20 出版日期:2020-02-25 发布日期:2020-03-04
通讯作者: 曾珏。E-mail:598722949@qq.com E-mail:598722949@qq.com
作者简介:徐世武(1973-),男,博士,副教授,主要从事资源环境遥感、GIS、国土信息化应用研究。E-mail:xushiwu1973@126.com
基金资助:
核查成果自动判别技术研究项目（2019114017）

A method of deep convolutional neural network photo classification for landuse scenes

XU Shiwu¹, ZENG Jue², ZHANG Shihui¹, LI Changzheng¹, LI Tingyu¹

1. School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China;
2. Chinese Land Surveying and Planning Institute, Beijing 100035, China

Received:2019-11-20 Online:2020-02-25 Published:2020-03-04

摘要/Abstract

摘要： 国土调查多角度实景举证照片具有视角多、分辨率高、层次丰富和剖面清晰的特点，透视且细致地刻画了土地利用图斑赋存状况和场景，弥补了遥感影像单一天顶视角的不足。本文基于语义分割提出了一种深度卷积神经网络（DCNN）实景照片土地利用场景分类方法，多语义标记照片场景，语义组合智能判定照片土地利用类别。该方法成功地应用在第三次国土调查照片自动核查工作中，减轻了人工判读工作量，提高了土地利用场景自动识别的精度。

关键词: 国土调查, 实景照片, 深度卷积神经网络, 多语义标记, 语义组合, 土地利用场景分类

Abstract: The multi-angle real-life proofed photos of the national land survey have multiple characteristics:high resolution, rich layers, and clear sections. The photos are accurate and detailed depictions of the occurrence status and scenes of landuse maps, which makes up for the lack of ground perspective of remote sensing images. Based on semantic segmentation, this paper proposes an innovative landuse scene classification method with a deep convolutional neural network (DCNN) for ground perspective photos. The method annotates photo scenes with multi-semantic technique and determines categories of photos of landuse with semantic composition. Successfully applied in the third automatic survey of land survey photos, this method reduces the workload of manual interpretation and improved the accuracy of automatic identification of landuse scenes.

Key words: land survey, real photos, deep convolutional neural networks, multiple semantic annotations, semantic composition, land use scenario classification

中图分类号:

P237

徐世武, 曾珏, 张诗慧, 李长征, 李亭谕. 一种深度卷积神经网络土地利用场景照片的分类方法[J]. 测绘通报, 2020, 0(2): 24-28,42.

XU Shiwu, ZENG Jue, ZHANG Shihui, LI Changzheng, LI Tingyu. A method of deep convolutional neural network photo classification for landuse scenes[J]. Bulletin of Surveying and Mapping, 2020, 0(2): 24-28,42.

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一种深度卷积神经网络土地利用场景照片的分类方法

A method of deep convolutional neural network photo classification for landuse scenes

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