收稿：2021-04-29，
纸质出版：2021-09-07
移动端阅览
高时空分辨率的全球多类别土地覆盖数据对于地球系统的生物化学循环、气候变化等研究至关重要。目前公开的数据产品中，较高空间分辨率的全球多类别土地覆盖产品仅提供单一或短时期的数据，而全球逐年土地覆盖产品往往只有单一土地覆盖类型，难以从较长时间跨度上反映精细地物的年际变化。本文借助Google Earth Engine平台，利用现有多套全球土地覆盖产品、Landsat卫星系列影像、以及大量人工目视解译样本，结合多数据融合、时序变化检测和机器学习等的方法，研制了一套2000年—2015年全球30 m分辨率的逐年土地覆盖变化数据集AGLC-2000-2015（Annual Global Land Cover 2000-2015）。基于AGLC-2000-2015数据集，本文选择性分析了3个典型区域（中国珠江三角洲地区、青藏高原色林错湖区和亚马逊热带雨林区）的土地覆盖年际变化。结果显示，AGLC-2000-2015数据集达到了较高的精度水平：基准年份产品（AGLC-2015）的总体精度（OA）为76.10%，Kappa系数为0.72，显著优于现有30 m分辨率的全球土地覆盖产品Globeland 30（OA = 63.49%，Kappa = 0.58）、FROM-GLC（OA = 61.41%，Kappa = 0.55）和GLC-FCS30（OA = 63.46%，Kappa = 0.57）；年际间分类模型的总体精度和Kappa系数分别为84.10%和0.81，在各大洲的平均总体精度均超过80.00%，表明该模型在全球多类别土地覆盖分类中表现良好。3个典型区域的土地覆盖变化分析显示，中国珠江三角洲地区城市扩张趋势明显（195.96 km
2
/a），其增量主要来源于耕地（84.88%）；青藏高原色林错湖泊对于气候变暖响应明显，湖区面积呈扩大趋势（17.95 km
2
/a），湖面北岸扩张最为明显；亚马逊热带雨林南部区域毁林造田趋势明显，15 a间森林面积减少46356.53 km
2
，其中大部分转化为农田（39621.29 km
2
）。上述结果表明：AGLC-2000-2015数据集能够有效反映全球陆地区域在30 m空间分辨率下的地表覆盖分布及年际间的动态演化，为地表陆面过程研究和相关应用提供可靠的数据支撑。
High-spatiotemporal-resolution global multi-class land cover data play a critical role in the studies of biogeochemical cycles of the Earth system and global climate change. Among the existing open products
higher-resolution global multi-class land cover data are available for a single or short period of time
while annual ones have limited class
preventing longer-term analysis of land cover change in fine spatial detail. Therefore
long time
high spatial resolution and high temporal frequency global land cover are needed.
In this paper
with the support of the Google Earth Engine platform
we proposed a method composed of data fusion
change detection and machine learning based on existing global land cover maps in 2015
Landsat imagery and samples after manual interpretation to develop annual global land cover data (Annual Global Land Cover-2000-2015) from 2000 to 2015 at 30 m resolution. Based on AGLC-2000-2015 data
we selectively analyzed dynamic change of land cover in three typical regions (the Pearl River Delta of China
Selin Co lake of Tibetan Plateau and the Amazon rainforest of Brazil).
Our results show relatively high accuracy of AGLC-2000-2015. Mean overall accuracy and Kappa coefficient of global land cover product for the year 2015 (AGLC-2015) are 76.10% and 0.72
respectively. The accuracies are considerably higher than that of existing global land covet products at 30m resolution
such as Globeland30 (OA=63.49%
Kappa=0.58)
FROM-GLC (OA=61.41%
Kappa=0.55)
and GLC-FCS30 (OA=63.46%
Kappa=0.57). The overall accuracy and Kappa coefficient of the Random Forest classification model are 84.10% and 0.81
respectively. In addition
the mean overall accuracy of Random Forest classification model at continental scale is more than 80.00%
showing that this model has good performance on global multi-class land cover mapping.
We analyzed the land cover changes for the 2000—2015 period in three selected regions. Urban area has increased substantially by an average of 195.96 km
2
in the Pearl River Delta of China
with 85% of the newly developed impervious surface encroaching on cropland. Selin Co lake responses significantly to the warming climate with expanding at a rate of 17.95 km
2
and the expansion is most pronounced in the north bank. Forest in the south part of Amazon has decreased by a total area of 46356.53 km
2
most of which is converted to cropland
showing forest destruction for cropland.
AGLC-2000-2015 can effectively reflect the distribution and annual change of global land cover classes at 30 m resolution from 2000 to 2015
providing fundamental data for research and application related to land surface processes.
Arino O , Bicheron P , Achard F , Latham J , Witt R and Weber J L . 2008 . GLOBCOVER: the most detailed portrait of Earth. European Space Agency Bulletin, (136): 24 - 31
Bartholome E and Belward A S . 2005 . GLC2000: a new approach to global land cover mapping from Earth observation data . International Journal of Remote Sensing , 26 ( 9 ): 1959 - 1977 [ DOI: 10.1080/01431160412331291297 http://dx.doi.org/10.1080/01431160412331291297 ]
Bontemps S , Defourny P , Van Bogaert E , Arino O , Kalogirou V and Perez J R . 2011 . Globcover 2009: products description and validation report [R/OL]. [ 2021-04-03 ]. http://due.esrin.esa.int/files/GLOBCOVER2009_Validation_Report_2.2.pdf http://due.esrin.esa.int/files/GLOBCOVER2009_Validation_Report_2.2.pdf
Bounoua L , DeFries R , Collatz G J , Sellers P and Khan H . 2002 . Effects of land cover conversion on surface climate . Climatic Change , 52 ( 1/2 ): 29 - 64 [ DOI: 10.1023/A:1013051420309 http://dx.doi.org/10.1023/A:1013051420309 ]
Chen J , Chen J , Gong P , Liao A P and He C Y . 2011 . Higher resolution global land cover mapping . Geomatics World , 9 ( 2 ): 12 - 14
陈军 , 陈晋 , 宫鹏 , 廖安平 , 何超英 . 2011 . 全球地表覆盖高分辨率遥感制图 . 地理信息世界 , 9 ( 2 ): 12- 14 [ DOI: 10.3969/j.issn.1672-1586.2011.02.002 http://dx.doi.org/10.3969/j.issn.1672-1586.2011.02.002 ]
Chen J , Chen J and Liao A P . 2016 . Global Land Cover Mapping . Beijing : Science Press : 145 - 149
陈军 , 陈晋 , 廖安平 . 2016 . 全球地表覆盖遥感制图 . 北京 : 科学出版社 : 145 - 149
Chen J , Chen J , Liao A P , Cao X , Chen L J , Chen X H , He C Y , Han G , Peng S , Lu M , Zhang W W , Tong X H and Mills J . 2015 . Global land cover mapping at 30 m resolution: a POK-based operational approach . ISPRS Journal of Photogrammetry and Remote Sensing , 103 : 7 - 27 [ DOI: 10.1016/j.isprsjprs.2014.09.002 http://dx.doi.org/10.1016/j.isprsjprs.2014.09.002 ]
Cohen W B , Healey S P , Yang Z Q , Stehman S V , Brewer C K , Brooks E B , Gorelick N , Huang C Q , Hughes M J , Kennedy R E , Loveland T R , Moisen G G , Schroeder T A , Vogelmann J E , Woodcock C E , Yang L M and Zhu Z . 2017 . How similar are forest disturbance maps derived from different Landsat time series algorithms? Forests , 8 ( 4 ): 98 [ DOI: 10.3390/f8040098 http://dx.doi.org/10.3390/f8040098 ]
De Sy V , Herold M , Achard F , Beuchle R , Clevers J G P W , Lindquist E and Verchot L . 2015 . Land use patterns and related carbon losses following deforestation in South America . Environmental Research Letters , 10 ( 12 ): 124004 [ DOI: 10.1088/1748-9326/10/12/124004 http://dx.doi.org/10.1088/1748-9326/10/12/124004 ]
Dempster A P . 1967 . Upper and lower probabilities induced by a multivalued mapping . The Annals of Mathematical Statistics , 38 ( 2 ): 325 - 339 [ DOI: 10.1214/aoms/1177698950 http://dx.doi.org/10.1214/aoms/1177698950 ]
Dong S Y , Xue X , You Q G and Peng F . 2014 . Remote sensing monitoring of the lake area changes in the Qinghai-Tibet Plateau in recent 40 years . Journal of Lake Sciences , 26 ( 4 ): 535 - 544
董斯扬 , 薛娴 , 尤全刚 , 彭飞 . 2014 . 近40年青藏高原湖泊面积变化遥感分析 . 湖泊科学 , 26 ( 4 ): 535- 544 [ DOI: 10.18307/2014.0407 http://dx.doi.org/10.18307/2014.0407 ]
ESA . 2017 . Land cover CCI product user guide version 2.0[M/OL] . [2021-05-19] . http://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf http://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf
Foley J A , DeFries R , Asner G P , Barford C , Bonan G , Carpenter S R , Chapin F S , Coe M T , Daily G C , Gibbs H K , Helkowski J H , Holloway T , Howard E A , Kucharik C J , Monfreda C , Patz J A , Prentice I C , Ramankutty N and Snyder P K . 2005 . Global consequences of land use . Science , 309 ( 5734 ): 570 - 574 [ DOI: 10.1126/science.1111772 http://dx.doi.org/10.1126/science.1111772 ]
Friedl M A , Sulla-Menashe D , Tan B , Schneider A , Ramankutty N , Sibley A and Huang X M . 2010 . MODIS Collection 5 global land cover: algorithm refinements and characterization of new datasets . Remote Sensing of Environment , 114 ( 1 ): 168 - 182 [ DOI: 10.1016/j.rse.2009.08.016 http://dx.doi.org/10.1016/j.rse.2009.08.016 ]
Fu P and Weng Q H . 2016 . A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery . Remote Sensing of Environment , 175 : 205 - 214 [ DOI: 10.1016/j.rse.2015.12.040 http://dx.doi.org/10.1016/j.rse.2015.12.040 ]
Gong P . 2021 . Intelligent mapping with remote sensing, iMap . National Remote Sensing Bulletin , 25 ( 2 ): 527 - 529
宫鹏 . 2021 . 智慧遥感制图(iMap) . 遥感学报 , 25 ( 2 ): 527- 529 [ DOI: 10.11834/jrs.20211010 http://dx.doi.org/10.11834/jrs.20211010 ]
Gong P , Li X C , Wang J , Bai Y Q , Chen B , Hu T Y , Liu X P , Xu B , Yang J , Zhang W and Zhou Y Y . 2020 . Annual maps of global artificial impervious area (GAIA) between 1985 and 2018 . Remote Sensing of Environment , 236 : 111510 [ DOI: 10.1016/j.rse.2019.111510 http://dx.doi.org/10.1016/j.rse.2019.111510 ]
Gong P , Liu H , Zhang M N , Li C C , Wang J , Huang H B , Clinton N , Ji L Y , Li W Y , Bai Y Q , Chen B , Xu B , Zhu Z L , Yuan C , Suen H P , Guo J , Xu N , Li W J , Zhao Y Y , Yang J , Yu C Q , Wang X , Fu H H , Yu L , Dronova I , Hui F M , Cheng X , Shi X L , Xiao F J , Liu Q F and Song L C . 2019 . Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017 . Science Bulletin , 64 ( 6 ): 370 - 373 [ DOI: 10.1016/j.scib.2019.03.002 http://dx.doi.org/10.1016/j.scib.2019.03.002 ]
Gong P , Wang J , Yu L , Zhao Y C , Zhao Y Y , Liang L , Niu Z G , Huang X M , Fu H H , Liu S , Li C C , Li X Y , Fu W , Liu C X , Xu Y , Wang X Y , Cheng Q , Hu L Y , Yao W B , Zhang H , Zhu P , Zhao Z Y , Zhang H Y , Zheng Y M , Ji L Y , Zhang Y W , Chen H , Yan A , Guo J H , Yu L , Wang L , Liu X J , Shi T T , Zhu M H , Chen Y L , Yang G W , Tang P , Xu B , Giri C , Clinton N , Zhu Z L , Chen J and Chen J . 2013 . Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data . International Journal of Remote Sensing , 34 ( 7 ): 2607 - 2654 [ DOI: 10.1080/01431161.2012.748992 http://dx.doi.org/10.1080/01431161.2012.748992 ]
Gorelick N , Hancher M , Dixon M , Ilyushchenko S , Thau D and Moore R . 2017 . Google earth engine: planetary-scale geospatial analysis for everyone . Remote Sensing of Environment , 202 : 18 - 27 [ DOI: 10.1016/j.rse.2017.06.031 http://dx.doi.org/10.1016/j.rse.2017.06.031 ]
Hansen M C , Defries R S , Townshend J R G and Sohlberg R . 2000 . Global land cover classification at 1km spatial resolution using a classification tree approach . International Journal of Remote Sensing , 21 ( 6/7 ): 1331 - 1364 [ DOI: 10.1080/014311600210209 http://dx.doi.org/10.1080/014311600210209 ]
Hansen M C , Potapov P V , Moore R , Hancher M , Turubanova S A , Tyukavina A , Thau D , Stehman S V , Goetz S J , Loveland T R , Kommareddy A , Egorov A , Chini L , Justice C O and Townshend J R G . 2013 . High-resolution global maps of 21st-century forest cover change . Science , 342 ( 6160 ): 850 - 853 [ DOI: 10.1126/science.1244693 http://dx.doi.org/10.1126/science.1244693 ]
Jiang W and Deng X Y . 2018 . Dempster-Shafer Evidence Theory: Information Modeling and Application . Beijing : Science Press : 8 - 11
蒋雯 , 邓鑫洋 . 2018 . D-S证据理论信息建模与应用 . 北京 : 科学出版社 : 8 - 11
Jung M , Henkel K , Herold M and Churkina G . 2006 . Exploiting synergies of global land cover products for carbon cycle modeling . Remote Sensing of Environment , 101 ( 4 ): 534 - 553 [ DOI: 10.1016/j.rse.2006.01.020 http://dx.doi.org/10.1016/j.rse.2006.01.020 ]
Lei Y B , Yao T D , Bird B W , Yang K , Zhai J Q and Sheng Y W . 2013 . Coherent lake growth on the central Tibetan Plateau since the 1970s: characterization and attribution . Journal of Hydrology , 483 : 61 - 67 [ DOI: 10.1016/j.jhydrol.2013.01.003 http://dx.doi.org/10.1016/j.jhydrol.2013.01.003 ]
Liu H and Gong P . 2021 . 21st century daily seamless data tube reconstruction and seasonal to annual land cover and land use dynamics . National Remote Sensing Bulletin , 25 ( 1 ): 126 - 147
刘涵 , 宫鹏 . 2021 . 21 世纪逐日无缝数据立方体构建方法及逐年逐季节土地覆盖和土地利用动态制图—中国智慧遥感制图iMap(China) 1 .0. 遥感学报, 25 ( 1 ), 126-147 [ DOI: 10.11834/jrs.20210580 http://dx.doi.org/10.11834/jrs.20210580 ]
Liu H , Gong P , Wang J , Wang X , Ning G and Xu B . 2021 . Production of global daily seamless data cubes and quantification of global land cover change from 1985 to 2020 -iMap World 1 .0. Remote Sensing of Environment, 258 ( 2 ): 112364 .
Liu L , Jiang L M , Xiang L W , Wang H S , Sun Y F and Xu H Z . 2019 . The effect of glacier melting on lake volume change in the Siling Co basin 5 Z 2
) , Tibetan Plateau . Chinese Journal of Geophysics , 62 ( 5 ): 1603 - 1612
柳林 , 江利明 , 相龙伟 , 汪汉胜 , 孙亚飞 , 许厚泽 . 2019 . 青藏高原色林错流域区冰川消融对湖泊水量变化的影响 . 地球物理学报 , 62 ( 5 ): 1603- 1612 [ DOI: 10.6038/cjg2019M0273 http://dx.doi.org/10.6038/cjg2019M0273 ]
Liu X P , Hu G H , Chen Y M , Li X , Xu X C , Li S Y , Pei F S and Wang S J . 2018 . High-resolution multi-temporal mapping of global urban land using Landsat images based on the Google Earth Engine platform . Remote Sensing of Environment , 209 : 227 - 239 [ DOI: 10.1016/j.rse.2018.02.055 http://dx.doi.org/10.1016/j.rse.2018.02.055 ]
Liu X P , Huang Y H , Xu X C , Li X C , Li X , Ciais P , Lin P R , Gong K , Ziegler A D , Chen A P , Gong P , Chen J , Hu G H , Chen Y M , Wang S J , Wu Q S , Huang K N , Estes L and Zeng Z Z . 2020 . High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015 . Nature Sustainability , 3 ( 7 ): 564 - 570 [ DOI: 10.1038/s41893-020-0521-x http://dx.doi.org/10.1038/s41893-020-0521-x ]
Loveland T R , Reed B C , Brown J F , Ohlen D O , Zhu Z , Yang L and Merchant J W . 2000 . Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data . International Journal of Remote Sensing , 21 ( 6/7 ): 1303 - 1330 [ DOI: 10.1080/014311600210191 http://dx.doi.org/10.1080/014311600210191 ]
Ludwig C , Walli A , Schleicher C , Weichselbaum J and Riffler M . 2019 . A highly automated algorithm for wetland detection using multi-temporal optical satellite data . Remote Sensing of Environment , 224 : 333 - 351 [ DOI: 10.1016/j.rse.2019.01.017 http://dx.doi.org/10.1016/j.rse.2019.01.017 ]
Malingreau J P , Eva H D and De Miranda E E . 2012 . Brazilian amazon: a significant five year drop in deforestation rates but figures are on the rise again . AMBIO , 41 ( 3 ): 309 - 314 [ DOI: 10.1007/s13280-011-0196-7 http://dx.doi.org/10.1007/s13280-011-0196-7 ]
Pekel J F , Cottam A , Gorelick N and Belward A S . 2016 . High-resolution mapping of global surface water and its long-term changes . Nature , 540 ( 7633 ): 418 - 422 [ DOI: 10.1038/nature20584 http://dx.doi.org/10.1038/nature20584 ]
Richards P D , Myers R J , Swinton S M and Walker R T . 2012 . Exchange rates, soybean supply response, and deforestation in South America . Global Environmental Change , 22 ( 2 ): 454 - 462 [ DOI: 10.1016/j.gloenvcha.2012.01.004 http://dx.doi.org/10.1016/j.gloenvcha.2012.01.004 ]
Roy D P , Kovalskyy V , Zhang H K , Vermote E F , Yan L , Kumar S S and Egorov A . 2016 . Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity . Remote Sensing of Environment , 185 : 57 - 70 [ DOI: 10.1016/j.rse.2015.12.024 http://dx.doi.org/10.1016/j.rse.2015.12.024 ]
Running S W . 2008 . Ecosystem disturbance, carbon, and climate . Science , 321 ( 5889 ): 652 - 653 [ DOI: 10.1126/science.1159607 http://dx.doi.org/10.1126/science.1159607 ]
Shafer G . 1976 . A Mathematical Theory of Evidence . Princeton : Princeton University Press : 5 - 7 [ DOI: 10.1515/9780691214696 http://dx.doi.org/10.1515/9780691214696 ]
Yan L J , Zheng M P and Wei L J . 2016 . Change of the lakes in Tibetan Plateau and its response to climate in the past forty years . Earth Science Frontiers , 23 ( 4 ): 310 - 323
闫立娟 , 郑绵平 , 魏乐军 . 2016 . 近40年来青藏高原湖泊变迁及其对气候变化的响应 . 地学前缘 , 23 ( 4 ): 310- 323 [ DOI: 10.13745/j.esf.2016.04.027 http://dx.doi.org/10.13745/j.esf.2016.04.027 ]
Zhang G Q . 2018 . Changes in lakes on the Tibetan Plateau observed from satellite data and their responses to climate variations . Progress in Geography , 37 ( 2 ): 214 - 223
张国庆 . 2018 . 青藏高原湖泊变化遥感监测及其对气候变化的响应研究进展 . 地理科学进展 , 37 ( 2 ): 214- 223 [ DOI: 10.18306/dlkxjz.2018.02.004 http://dx.doi.org/10.18306/dlkxjz.2018.02.004 ]
Zhang X , Liu L Y , Chen X D , Gao Y , Xie S and Mi J . 2021 . GLC_FCS30: global land-cover product with fine classification system at 30 m using time-series Landsat imagery . Earth System Science Data Discussion , 6 ( 13 ): 2753 - 2776 [ DOI: 10.5194/essd-2020-182 http://dx.doi.org/10.5194/essd-2020-182 ]
Zhu L P , Zhang G Q , Yang R M , Liu C , Yang K , Qiao B J and Han B P . 2019 . Lake variations on Tibetan Plateau of recent 40 years and future changing tendency . Bulletin of Chinese Academy of Sciences , 34 ( 11 ): 1254 - 1263
朱立平 , 张国庆 , 杨瑞敏 , 刘翀 , 阳坤 , 乔宝晋 , 韩博平 . 2019 . 青藏高原最近40年湖泊变化的主要表现与发展趋势 . 中国科学院院刊 , 34 ( 11 ): 1254- 1263 [ DOI: 10.16418/j.issn.1000-3045.2019.11.008 http://dx.doi.org/10.16418/j.issn.1000-3045.2019.11.008 ]
Zhu Z and Woodcock C E . 2014 . Continuous change detection and classification of land cover using all available Landsat data . Remote Sensing of Environment , 144 : 152 - 171 [ DOI: 10.1016/j.rse.2014.01.011 http://dx.doi.org/10.1016/j.rse.2014.01.011 ]
相关作者
相关机构
京公网安备11010802024621
