基于Google Earth Engine的红树林年际变化监测研究
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摘要
遥感技术已广泛应用于红树林资源调查与动态监测中,但仍然存在遥感数据获取困难、数据预处理工作量大、监测时间长而周期过大等问题,影响了学者对红树林演变过程的精细刻画与理解。本文基于Google Earth Engine(GEE)云遥感数据处理平台,选取Landsat系列卫星数据,生成长时间序列年际极少云影像集(云量少于5%),利用3个红外波段反射率(NIR、SWIR1、SWIR2)和3个特征指数(NDVI、NDWI、NDMI)建立阈值规则集,实现对实验区越南玉显县红树林、红树林-虾塘、不透水面-裸地、水体4种目标地物的专家知识决策树分类和土地覆盖的制图,并基于分类结果监测该区域1993-2017年的红树林年际动态变化。结果表明:GEE平台可满足多云多雨地区红树林的长时间序列年际变化监测需求;本文阈值分类方法可以有效提取红树林及红树林-虾塘,实验区有86%年份的影像分类精度达到80%以上;年际变化监测可精细刻画实验区红树林面积先增后减再增的变化过程,也能准确反映红树林与红树林-虾塘养殖系统面积之间的负相关关系。红树林年际动态监测结果可以降低红树林演变分析的不确定性,并能更精细地量化红树林与其他土地覆盖类型的转化过程,从而评估经济发展、政策等因素对红树林演变的影响。
Remote Sensing technologies have been widely used in the investigation and dynamics monitoring of mangrove forests. However, problems remained that severely hinder the precise description and deep understanding of mangrove forests' dynamics. The problems include difficulties in remotely sensed data acquisition, the heavy workload of data preprocessing, and the lengthy time period in long time series monitoring. Based on Google Earth Engine(GEE), a cloud platform of remotely sensed data processing, this study used raw images of Landsat series satellites to produce an inter-annual mostly-cloudless(cloud coverage less than 5%) image collection of top-of-atmosphere reflectance(TOA). Then, classification rules were established based on three infrared-band TOAs(NIR, band near infrared; SWIR1, band shortwave infrared 1; SWIR2, band shortwave infrared 2) and three indices(NDVI, normalized difference vegetation index; NDWI, normalized difference water index; NDMI, normalized difference moisture index). Next, four land cover types, i.e.,mangrove, mangrove-shrimp pond, impervious surface-bare land, and water body, were classified for mapping our case study area of Ngoc Hien, Vietnam from 1993 to 2017. Finally, the inter-annual land cover maps were used to analyze the characteristics of mangrove dynamics. The results showed that the long time-series interannual change monitoring of mangroves in cloudy and rainy regions can be implemented satisfactorily on the GEE platform. The image classification had an overall accuracy of over 80% for 86% of the study years,indicating that our proposed thresholds-based approach can effectively extract mangroves and mangrove-shrimp ponds. Through the analysis of inter-annual changes, the change process of mangroves in this region was depicted in details: it first increased, then decreased, and later, increased again. The correlation between the area changes of mangroves and mangrove-shrimp ponds was accurately detected to be negative. The inter-annual change monitoring of mangroves reduces the uncertainty of researching mangrove evolution processes, and quantifies in more details the conversions between mangroves and other land cover types. In so doing, the impacts of economic development, policies, and other factors on mangrove dynamics can then be assessed.
Remote Sensing technologies have been widely used in the investigation and dynamics monitoring of mangrove forests. However, problems remained that severely hinder the precise description and deep understanding of mangrove forests' dynamics. The problems include difficulties in remotely sensed data acquisition, the heavy workload of data preprocessing, and the lengthy time period in long time series monitoring. Based on Google Earth Engine(GEE), a cloud platform of remotely sensed data processing, this study used raw images of Landsat series satellites to produce an inter-annual mostly-cloudless(cloud coverage less than 5%) image collection of top-of-atmosphere reflectance(TOA). Then, classification rules were established based on three infrared-band TOAs(NIR, band near infrared; SWIR1, band shortwave infrared 1; SWIR2, band shortwave infrared 2) and three indices(NDVI, normalized difference vegetation index; NDWI, normalized difference water index; NDMI, normalized difference moisture index). Next, four land cover types, i.e.,mangrove, mangrove-shrimp pond, impervious surface-bare land, and water body, were classified for mapping our case study area of Ngoc Hien, Vietnam from 1993 to 2017. Finally, the inter-annual land cover maps were used to analyze the characteristics of mangrove dynamics. The results showed that the long time-series interannual change monitoring of mangroves in cloudy and rainy regions can be implemented satisfactorily on the GEE platform. The image classification had an overall accuracy of over 80% for 86% of the study years,indicating that our proposed thresholds-based approach can effectively extract mangroves and mangrove-shrimp ponds. Through the analysis of inter-annual changes, the change process of mangroves in this region was depicted in details: it first increased, then decreased, and later, increased again. The correlation between the area changes of mangroves and mangrove-shrimp ponds was accurately detected to be negative. The inter-annual change monitoring of mangroves reduces the uncertainty of researching mangrove evolution processes, and quantifies in more details the conversions between mangroves and other land cover types. In so doing, the impacts of economic development, policies, and other factors on mangrove dynamics can then be assessed.
引文
[1]李想,刘凯,朱远辉,等.基于资源三号影像的红树林物种分类研究[J].遥感技术与应用,2018,33(2):360-369.[Li X, Liu K, Zhu Y H, et al. Study on mangrove species classification based on ZY-3 image[J]. Remote Sensing Technology and Application, 2018,33(2):360-369.]
[2]王文卿,王瑁.中国红树林[M].北京:科学出版社,2007.[Wang W Q, Wang M. The mangroves of China[M]. Beijing:Science Press, 2007.]
[3]张乔民,隋淑珍.中国红树林湿地资源及其保护[J].自然资源学报,2001,16(1):28-36.[Zhang Q M, Sui S Z. The mangrove wetland resources and their conservation in China[J]. Journal of Natural Resources, 2001,16(1):28-36.]
[4] Ha T T T, Van D H, Bush S R. Mangrove conservation or shrimp farmer's livelihood? The devolution of forest management and benefit sharing in the Mekong Delta, Vietnam[J]. Ocean&Coastal Management, 2012,69:185-193.
[5] Nurkin B. Degradation of mangrove forests in South Sulawesi, Indonesia[J]. Hydrobiologia, 1994,285(1-3):271-276.
[6] Valiela I, Bowen J L, York J K. Mangrove forests:One of the world's threatened major tropical environments[J].AIBS Bulletin, 2001,51(10):807-815.
[7] Richards D R, Friess D A. Rates and drivers of mangrove deforestation in Southeast Asia, 2000-2012[J]. Proceedings of the National Academy of Sciences, 2016,113(2):344-349.
[8] Cárdenas N Y, Joyce K E, Maier S W. Monitoring mangrove forests:Are we taking full advantage of technology?[J]. International Journal of Applied Earth Observation and Geoinformation, 2017,63:1-14.
[9] Son N, Chen C, Chang N, et al. Mangrove mapping and change detection in Ca Mau Peninsula, Vietnam, using Landsat data and object-based image analysis[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015,8(2):503-510.
[10] Tran L X, Fischer A. Spatiotemporal changes and fragmentation of mangroves and its effects on fish diversity in Ca Mau Province(Vietnam)[J]. Journal of Coastal Conservation, 2017,21(3):355-368.
[11] Van T T, Wilson N, Thanh-Tung H, et al. Changes in mangrove vegetation area and character in a war and land use change affected region of Vietnam(Mui Ca Mau)over six decades[J]. Acta Oecologica, 2015,63:71-81.
[12] Hauser L T, Vu G N, Nguyen B A, et al. Uncovering the spatio-temporal dynamics of land cover change and fragmentation of mangroves in the Ca Mau peninsula, Vietnam using multi-temporal SPOT satellite imagery(2004-2013)[J]. Applied Geography, 2017,86:197-207.
[13]王九中,田海峰,邬明权,等.河南省冬小麦快速遥感制图[J].地球信息科学学报,2017,19(6):846-853.[Wang J Z,Tian H F, Wu M Q, et al. Rapid mapping of winter wheat in Henan Province[J]. Journal of Geo-information Science, 2017,19(6):846-853.]
[14] Gorelick N, Hancher M, Dixon M, et al. Google Earth Engine:Planetary-scale geospatial analysis for everyone[J].Remote Sensing of Environment, 2017,202:18-27.
[15]徐晗泽宇,刘冲,王军邦,等. Google Earth Engine平台支持下的赣南柑橘果园遥感提取研究[J].地球信息科学学报,2018,20(3):396-404.[Xu H Z Y, Liu C, Wang J B, et al. Study on extraction of citrus orchard in Gannan Region based on Google Earth Engine platform[J]. Journal of Geo-information Science, 2018,20(3):396-404.]
[16] Shelestov A, Lavreniuk M, Kussul N, et al. Exploring Google Earth Engine platform for big data processing:Classification of multi-temporal satellite imagery for crop mapping[J]. Frontiers in Earth Science, 2017,5:17.
[17]郝斌飞,韩旭军,马明国,等. Google Earth Engine在地球科学与环境科学中的应用研究进展[J].遥感技术与应用,2018,33(4):600-611.[Hao B F, Han X J, Ma M G, et al. Research progress on the application of Google Earth Engine in geoscience and environmental sciences[J]. Remote Sensing Technology and Application, 2018,33(4):600-611.]
[18] Xiong J, Thenkabail P, Tilton J, et al. Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8data on Google Earth Engine[J]. Remote Sensing, 2017,9(10):1065.
[19] Kumar L, Mutanga O. Google Earth Engine applications since inception:Usage, trends, and potential[J]. Remote Sensing, 2018,10(10):1509.
[20] Hansen M C, Potapov P V, Moore R, et al. High-resolution global maps of 21st-century forest cover change[J].Science, 2013,342(6160):850-853.
[21] Reiche J, Lucas R, Mitchell A L, et al. Combining satellite data for better tropical forest monitoring[J]. Nature Climate Change, 2016,6(2):120-122.
[22] Xiong J, Thenkabail P S, Gumma M K, et al. Automated cropland mapping of continental Africa using Google Earth Engine cloud computing[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017,126:225-244.
[23] Liu X, Hu G, Chen Y, et al. High-resolution multi-temporal mapping of global urban land using Landsat images based on the Google Earth Engine Platform[J]. Remote Sensing of Environment, 2018,209:227-239.
[24] Chen B, Xiao X, Li X, et al. A mangrove forest map of China in 2015:Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017,131:104-120.
[25]周梅,李春干,代华兵.红树林空间分布遥感监测精度的影响因素及应对措施[J].南京林业大学学报(自然科学版),2018,1(42):163-168.[Zhou M, Li C G, Dai H B. Influence factors and measures of remote sensing monitoring precision of mangrove space distribution[J]. Journal of Nanjing Forestry University(Natural Sciences Edition), 2018,42(1):163-168.]
[26] Binh C T, Phillips M J, Demaine H. Integrated shrimpmangrove farming systems in the Mekong Delta of Vietnam[J]. Aquaculture Research, 1997,28(8):599-610.
[27] Sinh L X. Mangrove forests and shrimp culture in Ngoc Hien District, Minh Hai Province, Vietnam[J]. Naga,1994,17(4):15-16.
[28] Beveridge M C M, Phillips M J, Macintosh D J. Aquaculture and the environment:The supply of and demand for environmental goods and services by Asian aquaculture and the implications for sustainability[J]. Aquaculture Research, 1997,28(10):797-807.
[29]维基百科.玉显县[EB/OL]. https://zh.wikipedia.org/wiki/%E7%8E%89%E9%A1%AF%E7%B8%A3, 2017-10-31.[Wei J. https://en.wikipedia.org/wiki/Ng%E1%BB%8Dc_Hi%E1%BB%83n_District, 2017-10-31.]
[30] Baumgartner U, Nguyen T H. Organic certification for shrimp value chains in Ca Mau, Vietnam:A means for improvement or an end in itself?[J]. Environment, Development and Sustainability, 2017,19(3):987-1002.
[31]徐涵秋,王美雅.地表不透水面信息遥感的主要方法分析[J].遥感学报,2016,20(5):1270-1289.[Xu H Q, Wang M Y.Remote sensing-based retrieval of ground impervious surfaces[J]. Journal of Remote Sensing, 2016,20(5):1270-1289.]
[32] Chander G, Markham B L, Helder D L. Summary of current radiometric calibration coefficients for Landsat MSS,TM, ETM+, and EO-1 ALI sensors[J]. Remote Sensing of Environment, 2009,113(5):893-903.
[33] Salomonson V V, Appel I. Estimating fractional snow cover from MODIS using the normalized difference snow index[J]. Remote Sensing of Environment, 2004,89(3):351-360.
[34] Hamilton S E, Casey D. Creation of a high spatio-temporal resolution global database of continuous mangrove forest cover for the 21st century(CGMFC-21)[J]. Global Ecology and Biogeography, 2016,25(6):729-738.
[35] Hyndman R J, Athanasopoulos G. Forecasting:Principles and practice(2nd ed)[M]. Melbourne:OTexts, 2018.
[36] Rouse J J W, Haas R H, Schell J A, et al. Monitoring vegetation systems in the Great Plains with ERTS[J]. NASA Special Publication, 1974,351:309.
[37] Mc Feeters S K. The use of the Normalized Difference Water Index(NDWI)in the delineation of open water features[J].International Journal of Remote Sensing, 1996,17(7):1425-1432.
[38] Wilson E H, Sader S A. Detection of forest harvest type using multiple dates of Landsat TM imagery[J]. Remote Sensing of Environment, 2002,80(3):385-396.
[39]赵英时.遥感应用分析原理与方法(第二版)[M].北京:科学出版社,2013.[Zhao Y S. Analysis principles and methods on remote sensing application(2nd ed)[M]. Beijing:Science Press, 2013.]
[40] Beresnev N N, Phung T, Broadhead J. Mangrove-related policy and institutional frameworks in Pakistan, Thailand and Viet Nam[M]. Bangkok:Food and Agriculture Organization of the United Nations Regional Office for Asia and the Pacific, International Union for Conservation of Nature, 2016.
[41] Ha T T T, Bush S R, Mol A P J, et al. Organic coasts? Regulatory challenges of certifying integrated shrimp-mangrove production systems in Vietnam[J]. Journal of Rural Studies, 2012,28(4):631-639.
[2]王文卿,王瑁.中国红树林[M].北京:科学出版社,2007.[Wang W Q, Wang M. The mangroves of China[M]. Beijing:Science Press, 2007.]
[3]张乔民,隋淑珍.中国红树林湿地资源及其保护[J].自然资源学报,2001,16(1):28-36.[Zhang Q M, Sui S Z. The mangrove wetland resources and their conservation in China[J]. Journal of Natural Resources, 2001,16(1):28-36.]
[4] Ha T T T, Van D H, Bush S R. Mangrove conservation or shrimp farmer's livelihood? The devolution of forest management and benefit sharing in the Mekong Delta, Vietnam[J]. Ocean&Coastal Management, 2012,69:185-193.
[5] Nurkin B. Degradation of mangrove forests in South Sulawesi, Indonesia[J]. Hydrobiologia, 1994,285(1-3):271-276.
[6] Valiela I, Bowen J L, York J K. Mangrove forests:One of the world's threatened major tropical environments[J].AIBS Bulletin, 2001,51(10):807-815.
[7] Richards D R, Friess D A. Rates and drivers of mangrove deforestation in Southeast Asia, 2000-2012[J]. Proceedings of the National Academy of Sciences, 2016,113(2):344-349.
[8] Cárdenas N Y, Joyce K E, Maier S W. Monitoring mangrove forests:Are we taking full advantage of technology?[J]. International Journal of Applied Earth Observation and Geoinformation, 2017,63:1-14.
[9] Son N, Chen C, Chang N, et al. Mangrove mapping and change detection in Ca Mau Peninsula, Vietnam, using Landsat data and object-based image analysis[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015,8(2):503-510.
[10] Tran L X, Fischer A. Spatiotemporal changes and fragmentation of mangroves and its effects on fish diversity in Ca Mau Province(Vietnam)[J]. Journal of Coastal Conservation, 2017,21(3):355-368.
[11] Van T T, Wilson N, Thanh-Tung H, et al. Changes in mangrove vegetation area and character in a war and land use change affected region of Vietnam(Mui Ca Mau)over six decades[J]. Acta Oecologica, 2015,63:71-81.
[12] Hauser L T, Vu G N, Nguyen B A, et al. Uncovering the spatio-temporal dynamics of land cover change and fragmentation of mangroves in the Ca Mau peninsula, Vietnam using multi-temporal SPOT satellite imagery(2004-2013)[J]. Applied Geography, 2017,86:197-207.
[13]王九中,田海峰,邬明权,等.河南省冬小麦快速遥感制图[J].地球信息科学学报,2017,19(6):846-853.[Wang J Z,Tian H F, Wu M Q, et al. Rapid mapping of winter wheat in Henan Province[J]. Journal of Geo-information Science, 2017,19(6):846-853.]
[14] Gorelick N, Hancher M, Dixon M, et al. Google Earth Engine:Planetary-scale geospatial analysis for everyone[J].Remote Sensing of Environment, 2017,202:18-27.
[15]徐晗泽宇,刘冲,王军邦,等. Google Earth Engine平台支持下的赣南柑橘果园遥感提取研究[J].地球信息科学学报,2018,20(3):396-404.[Xu H Z Y, Liu C, Wang J B, et al. Study on extraction of citrus orchard in Gannan Region based on Google Earth Engine platform[J]. Journal of Geo-information Science, 2018,20(3):396-404.]
[16] Shelestov A, Lavreniuk M, Kussul N, et al. Exploring Google Earth Engine platform for big data processing:Classification of multi-temporal satellite imagery for crop mapping[J]. Frontiers in Earth Science, 2017,5:17.
[17]郝斌飞,韩旭军,马明国,等. Google Earth Engine在地球科学与环境科学中的应用研究进展[J].遥感技术与应用,2018,33(4):600-611.[Hao B F, Han X J, Ma M G, et al. Research progress on the application of Google Earth Engine in geoscience and environmental sciences[J]. Remote Sensing Technology and Application, 2018,33(4):600-611.]
[18] Xiong J, Thenkabail P, Tilton J, et al. Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8data on Google Earth Engine[J]. Remote Sensing, 2017,9(10):1065.
[19] Kumar L, Mutanga O. Google Earth Engine applications since inception:Usage, trends, and potential[J]. Remote Sensing, 2018,10(10):1509.
[20] Hansen M C, Potapov P V, Moore R, et al. High-resolution global maps of 21st-century forest cover change[J].Science, 2013,342(6160):850-853.
[21] Reiche J, Lucas R, Mitchell A L, et al. Combining satellite data for better tropical forest monitoring[J]. Nature Climate Change, 2016,6(2):120-122.
[22] Xiong J, Thenkabail P S, Gumma M K, et al. Automated cropland mapping of continental Africa using Google Earth Engine cloud computing[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017,126:225-244.
[23] Liu X, Hu G, Chen Y, et al. High-resolution multi-temporal mapping of global urban land using Landsat images based on the Google Earth Engine Platform[J]. Remote Sensing of Environment, 2018,209:227-239.
[24] Chen B, Xiao X, Li X, et al. A mangrove forest map of China in 2015:Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017,131:104-120.
[25]周梅,李春干,代华兵.红树林空间分布遥感监测精度的影响因素及应对措施[J].南京林业大学学报(自然科学版),2018,1(42):163-168.[Zhou M, Li C G, Dai H B. Influence factors and measures of remote sensing monitoring precision of mangrove space distribution[J]. Journal of Nanjing Forestry University(Natural Sciences Edition), 2018,42(1):163-168.]
[26] Binh C T, Phillips M J, Demaine H. Integrated shrimpmangrove farming systems in the Mekong Delta of Vietnam[J]. Aquaculture Research, 1997,28(8):599-610.
[27] Sinh L X. Mangrove forests and shrimp culture in Ngoc Hien District, Minh Hai Province, Vietnam[J]. Naga,1994,17(4):15-16.
[28] Beveridge M C M, Phillips M J, Macintosh D J. Aquaculture and the environment:The supply of and demand for environmental goods and services by Asian aquaculture and the implications for sustainability[J]. Aquaculture Research, 1997,28(10):797-807.
[29]维基百科.玉显县[EB/OL]. https://zh.wikipedia.org/wiki/%E7%8E%89%E9%A1%AF%E7%B8%A3, 2017-10-31.[Wei J. https://en.wikipedia.org/wiki/Ng%E1%BB%8Dc_Hi%E1%BB%83n_District, 2017-10-31.]
[30] Baumgartner U, Nguyen T H. Organic certification for shrimp value chains in Ca Mau, Vietnam:A means for improvement or an end in itself?[J]. Environment, Development and Sustainability, 2017,19(3):987-1002.
[31]徐涵秋,王美雅.地表不透水面信息遥感的主要方法分析[J].遥感学报,2016,20(5):1270-1289.[Xu H Q, Wang M Y.Remote sensing-based retrieval of ground impervious surfaces[J]. Journal of Remote Sensing, 2016,20(5):1270-1289.]
[32] Chander G, Markham B L, Helder D L. Summary of current radiometric calibration coefficients for Landsat MSS,TM, ETM+, and EO-1 ALI sensors[J]. Remote Sensing of Environment, 2009,113(5):893-903.
[33] Salomonson V V, Appel I. Estimating fractional snow cover from MODIS using the normalized difference snow index[J]. Remote Sensing of Environment, 2004,89(3):351-360.
[34] Hamilton S E, Casey D. Creation of a high spatio-temporal resolution global database of continuous mangrove forest cover for the 21st century(CGMFC-21)[J]. Global Ecology and Biogeography, 2016,25(6):729-738.
[35] Hyndman R J, Athanasopoulos G. Forecasting:Principles and practice(2nd ed)[M]. Melbourne:OTexts, 2018.
[36] Rouse J J W, Haas R H, Schell J A, et al. Monitoring vegetation systems in the Great Plains with ERTS[J]. NASA Special Publication, 1974,351:309.
[37] Mc Feeters S K. The use of the Normalized Difference Water Index(NDWI)in the delineation of open water features[J].International Journal of Remote Sensing, 1996,17(7):1425-1432.
[38] Wilson E H, Sader S A. Detection of forest harvest type using multiple dates of Landsat TM imagery[J]. Remote Sensing of Environment, 2002,80(3):385-396.
[39]赵英时.遥感应用分析原理与方法(第二版)[M].北京:科学出版社,2013.[Zhao Y S. Analysis principles and methods on remote sensing application(2nd ed)[M]. Beijing:Science Press, 2013.]
[40] Beresnev N N, Phung T, Broadhead J. Mangrove-related policy and institutional frameworks in Pakistan, Thailand and Viet Nam[M]. Bangkok:Food and Agriculture Organization of the United Nations Regional Office for Asia and the Pacific, International Union for Conservation of Nature, 2016.
[41] Ha T T T, Bush S R, Mol A P J, et al. Organic coasts? Regulatory challenges of certifying integrated shrimp-mangrove production systems in Vietnam[J]. Journal of Rural Studies, 2012,28(4):631-639.
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