1995—2019年北莉岛人工水产养殖遥感监测

doi:10.13474/j.cnki.11-2246.2022.0194

摘要/Abstract

摘要： 有效监测人工水产养殖水面的分布变化对于海洋资源管理、生态环境保护、防灾减灾具有重要意义。本文以Landsat 5、SPOT 5和GF-1卫星影像为数据源,选择广东省北莉岛为研究区,使用线性光谱解混方法获取中等空间分辨率卫星影像的人工水产养殖水面面积,通过面向对象多尺度分割的方法结合支持向量机分类算法提取高空间分辨率卫星影像的人工水产养殖水面分布。研究结果表明,与单一卫星影像相比,综合多源中高空间分辨率卫星数据延长了人工水产养殖水面变化分析可追溯的时间跨度,提高了监测精度;联合光谱解混和面向对象分类方法开展人工水产养殖长时序遥感监测是可行的。近20多年来,北莉岛人工水产养殖水面的面积经历了先增加后缓慢减少的变化过程,1995—2000年平均增速为23.39 hm²/a,2000—2006年平均增速为23.95 hm²/a,2006—2019年平均减少速度为1.96 hm²/a。

关键词: 水产养殖, 面向对象, 光谱解混, 国产高分卫星, 遥感

Abstract: It is of great significance to monitor coastal aquaculture ponds, especially for marine resource management, ecological environment protection, disaster prevention and mitigation. This paper uses Landsat 5, SPOT 5 and GF-1 satellite imagery as data source, and selects Beili island in Guangdong province as the research area. Linear spectral unmixing method is applied to obtain the area of coastal aquaculture ponds based on medium spatial resolution satellite imagery, whereas object-oriented multi-scale segmentation and support vector machine classification algorithm is used to extract coastal aquaculture ponds based on high spatial resolution satellite imagery. The results demonstrate that compared with a single satellite data source, the multi-source medium and high spatial resolution satellite imagery extends the traceable time span of the coastal aquaculture water surface change analysis and improves the monitoring accuracy; the combined spectral unmixing and object-oriented classification methods can be used to monitor coastal aquaculture ponds for long time series. In the past two decades, the area of coastal aquaculture ponds in Beili island first increased and then slowly decreased. The average growth rate of the coastal aquaculture pond area is 23.39 hm² from 1995 to 2000, 23.95 hm²/a from 2000 to 2006, and -1.96 hm²/a from 2019 to 2006.

Key words: coastal aquaculture, object-orientation, spectral unmixing, domestic high spatial resolution satellite, remote sensing

中图分类号:

P237

董迪, 魏征, 曾纪胜. 1995—2019年北莉岛人工水产养殖遥感监测[J]. 测绘通报, 2022, 0(7): 1-6.

DONG Di, WEI Zheng, ZENG Jisheng. Remote sensing monitoring of coastal aquaculture ponds in Beili island from 1995 to 2019[J]. Bulletin of Surveying and Mapping, 2022, 0(7): 1-6.

参考文献

[1] 蒋逸明,董迪,岳文,等.基于多源高分遥感影像的围海养殖动态监测[J].海洋信息, 2021, 36(1):40-45.
[2] 程博,刘岳明,刘旭楠,等.基于多源特征融合的高分辨率遥感图像近海养殖区提取方法研究[J].遥感技术与应用, 2018, 33(2):296-304.
[3] 关学彬,张翠萍,蒋菊生,等.水产养殖遥感监测及信息自动提取方法研究[J].国土资源遥感, 2009, 21(2):41-44.
[4] 黄森文,韦春竹.广东省沿海城市人工水产养殖基地变化:基于2015-2019年Sentinel-1数据的实证研究[J].热带地理, 2021, 41(3):622-634.
[5] 吴岩峻,张京红,田光辉,等.利用遥感技术进行海南省水产养殖调查[J].热带作物学报, 2006, 27(2):108-111.
[6] 孙裕钰,应警亮,王梅,等.面向对象的围海养殖用海信息分类提取与动态监测研究[J].海洋信息, 2016(2):6-11.
[7] 卢业伟,李强子,杜鑫,等.基于高分辨率影像的近海养殖区的一种自动提取方法[J].遥感技术与应用, 2015, 30(3):486-494.
[8] 徐京萍,赵建华,张丰收,等.面向对象的池塘养殖用海信息提取[J].国土资源遥感, 2013, 25(1):82-85.
[9] 宗玮.上海海岸带土地利用/覆盖格局变化及驱动机制研究[D].上海:华东师范大学, 2012.
[10] 梁建平.双台河口国际重要湿地景观动态及人类活动影响遥感评估[D].赣州:江西理工大学, 2015.
[11] HASHEM S, AKTER T, SALAM M A, et al.Aquaculture planning through remote sensing image analysis and GIS tools in Northeast region, Bangladesh[J].International Journal of Fisheries and Aquatic Studies, 2014,1(5):134-143.
[12] CHEN Yuanyuan, HE Xiufeng, WANG Jing, et al.The influence of polarimetric parameters and an object-based approach on land cover classification in coastal wetlands[J].Remote Sensing, 2014, 6(12):12575-12592.
[13] OTTINGER M, CLAUSS K, KUENZER C.Large-scale assessment of coastal aquaculture ponds withsentinel-1 time series data[J].Remote Sensing, 2017, 9(5):440.
[14] REN Chunying, WANG Zongming, ZHANG Bai, et al.Remote monitoring of expansion of aquaculture ponds along coastal region of the Yellow River Delta from 1983 to 2015[J].Chinese Geographical Science, 2018, 28(3):430-442.
[15] DUAN Yuanqiang, LI Xing, ZHANG Lianpeng, et al.Mapping national-scale aquaculture ponds based on the Google Earth Engine in the Chinese coastal zone[J].Aquaculture, 2020, 520:734666.
[16] DUAN Yuanqiang, LI Xing, ZHANG Lianpeng,et al.Detecting spatiotemporal changes of large-scale aquaculture ponds regions over 1988-2018 in Jiangsu Province, China using Google Earth Engine[J].Ocean&Coastal Management, 2020,188:105144.
[17] DUAN Yuanqiang, TIAN Bo, LI Xing, et al.Tracking changes in aquaculture ponds on the China coast using 30 years of Landsat images[J].International Journal of Applied Earth Observation and Geoinformation, 2021, 102:102383.
[18] STILLER D, OTTINGER M, LEINENKUGEL P.Spatio-temporal patterns of coastal aquaculture derived from Sentinel-1 time series data and the full landsat archive[J].Remote Sensing, 2019, 11(14):1707.
[19] JARCHOW C J, SIGAFUS B H, MUTHS E, et al.Using full and partial unmixing algorithms to estimate the inundation extent of small, isolated stock ponds in an arid landscape[J].Wetlands, 2020, 40(3):563-575.
[20] 任德智,周尧治,李江荣,等.Pleiades-1高分辨率影像像素级4种融合算法的综合评价研究[J].西部林业科学, 2014, 43(1):34-39.
[21] BAATZ M,SCHÄPE A.Object-oriented and multi-scale image analysis in semantic networks[J].2nd International Symposium:Operationalization of Remote Sensing, 1999:1-7.
[22] 吴剑.基于面向对象技术的遥感震害信息提取与评价方法研究[D].武汉:武汉大学, 2010.
[23] HALABISKY M, MOSKAL L M, GILLESPIE A, et al.Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984-2011)[J].Remote Sensing of Environment, 2016, 177:171-183.
[24] 孔美美.基于混合像元分解的水体提取及变化监测研究[D].泉州:华侨大学, 2016.
[25] 黄进,张再漾.徐闻北莉村:30载靠海谋生路[J].农村农业农民(A版), 2014(5):39-41.