| 连云港近海紫菜养殖区遥感识别、空间变异和驱动分析 |
| |
| 引用本文： | 卢 霞,顾 杨,王晓静,林雅丽,赵 倩,王 凯,刘笑楠,费鲜芸.连云港近海紫菜养殖区遥感识别、空间变异和驱动分析[J].海洋科学,2018,42(7):87-96. |
| |
| 作者姓名： | 卢 霞 顾 杨 王晓静 林雅丽 赵 倩 王 凯 刘笑楠 费鲜芸 |
| |
| 作者单位： | 淮海工学院 测绘与海洋信息学院,淮海工学院 测绘与海洋信息学院,淮海工学院 测绘与海洋信息学院,淮海工学院 测绘与海洋信息学院,淮海工学院 测绘与海洋信息学院,淮海工学院 测绘与海洋信息学院,淮海工学院 测绘与海洋信息学院,淮海工学院 测绘与海洋信息学院 |
| |
| 基金项目： | 江苏省测绘地理信息局科研项目(JSCHKY201709); 国家自然科学基金资助项目(41506106, 31270745); 连云港市科技计划重大项目(CN1510); 海岸带地理环境监测国家测绘地理信息局重点实验室开放基金资助项目(GE-2017-003); 江苏省研究生实践创新计划项目(SJCX17_0706); 江苏省海洋技术品牌专业建设项目(PPZY2015B116) |
| |
| 摘 要： | 为了科学有效地掌握海域使用信息、管理海域权属,为海域资源调查、管理、规划、保护、合理利用提供服务,为违法、违规、违章用海项目得到有效遏制,减少用海矛盾,有必要开展海域使用动态监测,作者以连云港近海为研究区,利用4个时相Landsat遥感影像(2002、2008、2013、2016年)通过面向对象算法提取弱水背景下的紫菜养殖区信息,揭示空间分异规律,并分析其驱动原因。研究结果表明:4期影像提取连云港近海紫菜养殖区信息的精度分别是87.5%、92%、91.7%和94.6%。紫菜养殖区空间分布的变化规律为紫菜养殖面积不断增加且整体向深海方向推进。赣榆港口航运区和田湾核电站特殊利用区存在少量紫菜养殖区,项目用海不符合连云港市海洋功能区划(2016～2020年)。连云港近海紫菜养殖区空间分异的驱动因子主要是自然条件、养殖技术、海洋经济和社会发展四大因素。
|
| 关 键 词： | 连云港 紫菜养殖区 面向对象 空间分布 驱动因素 |
| 收稿时间： | 2018/4/1 0:00:00 |
| 修稿时间： | 2018/6/1 0:00:00 |
The identification of Porphyra culture area by remote sensing and spatial distribution change and driving factors analysis |
| |
| LU Xi,GU Yang,WANG Xiao-jing,LIN Ya-li,ZHAO Qian,WANG Kai,LIU Xiao-nan and FEI Xian-yun.The identification of Porphyra culture area by remote sensing and spatial distribution change and driving factors analysis[J].Marine Sciences,2018,42(7):87-96. |
| |
| Authors: | LU Xi GU Yang WANG Xiao-jing LIN Ya-li ZHAO Qian WANG Kai LIU Xiao-nan and FEI Xian-yun |
| |
| Abstract: | It is necessary to perform dynamic monitoring of sea area usage in order to grasp sea area usage status, manage sea area rights, carry out the investigation, management, planning, protection, and utilization of marine resources, and reduce the illegal sea usage projects. Lianyungang sea was taken as the subject investigated and Porphyra culture area information under the sea water was retrieved based on four Landsat images (2002/2008/2013/2016a) by using object-oriented algorithm. Further, spatial distribution change and the driving factors were analyzed. Research results were indicated that the accuracy of Porphyra culture area identification were 87.5%, 92%, 91.7%, and 94.6% respectively. Spatial distribution pattern was that the total area of Porphyra culture increased and expanded from near-shore to offshore. Some Porphyra culture occupied the part of Ganyu port shipping function zone and special utilization zone of Tianwan nuclear power station. It was inconsistent with Lianyungang marine functional regionalization (2016-2020). The primary driving factors were natural condition, cultivation techniques, marine economy, and social development. |
| |
| Keywords: | Lianyungang Porphyra culture area object-oriented algorithm spatial distribution driving factors |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《海洋科学》浏览原始摘要信息 |
| 点击此处可从《海洋科学》下载免费的PDF全文 |
|
