Remote sensing investigation and analysis of wetland in Gansu section of Heihe River Basin in the past 14 years

doi:10.6046/gtzyyg.2017.03.16

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Abstract In this study, the authors used the data of TM and ETM remote sensing images, geographical condition census data and water conservation census data obtained in 2000, 2008 and 2013 and multi-year statistic data as the main data sources. Using remote sensing and GIS technology, combined with the field survey, the authors systematically studied the types, sizes, composition and distribution of wetland resources in Gansu section of Heihe River Basin. The results show that the area of wetland in the study area is decreasing, slowdown was faster before 2008, and slowdown is significantly slower since 2008. The change of wetland resources results from natural factors and human activities. Among them, the impact of the main factors on the changes of wetland resources in the area is precipitation, temperature, upstream water, discharge and permafrost. Human factors are becoming more and more obvious in the change of wetland resources as an external force. The change of population quantity and the intensity of the land reform and utilization are the most active and direct factors influencing the wetland landscape. Government decision making and the restoration project of wetland protection have played a role in promoting the evolution of wetland resources.

Keywords marker-based watershed color histogram LBP textural feature region merging

Issue Date: 15 August 2017

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	MA Guorui
	MA Yanli
	JIANG Manzhen

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MA Guorui,MA Yanli,JIANG Manzhen. Remote sensing investigation and analysis of wetland in Gansu section of Heihe River Basin in the past 14 years[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(3): 111-117.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2017.03.16 OR https://www.gtzyyg.com/EN/Y2017/V29/I3/111

[1] 李伟,崔丽娟,张曼胤,等.基于3S技术的中国红树林湿地监测研究概述[J].湿地科学与管理,2008,4(2):60-64.
Li W,Cui L J,Zhang M Y,et al.A review of monitoring mangrove forest using 3S technologies in China[J].Wetland Science & Management,2008,4(2):60-64.
[2] 陈趁新,胡昌苗,霍连志,等.Landsat TM数据不同辐射校正方法对土地覆盖遥感分类的影响[J].遥感学报,2014,18(2):320-334.
Chen C X,Hu C M,Huo L Z,et al.Effect of different radiation correction methods of Landsat TM data on land-cover remote sensing classification[J].Journal of Remote Sensing,2014,18(2):320-334.
[3] 国地普发(2013)1号,第一次全国地理国情普查总体方案[EB/OL].[2013-09-17].http://zgchnj.sbsm.gov.cn/article/ljnjll/elysj/tz/zywx/201409/20140900017459.shtml.
File of the First Census Office 2013(1),The First Census Programme[EB/OL].[2013-09-17].http://zgchnj.sbsm.gov.cn/article/ljnjll/elysj/tz/zywx/201409/20140900017459.shtml.
[4] 张芳,塔西甫拉提·特依拜,熊黑钢,等.干旱区湿地信息的指数提取方法[J].干旱区地理,2011,34(6):983-989.
Zhang F,Tiyip T,Xiong H G,et al.Extracting wetlands information of arid zone based on index method[J].Arid Land Geography,2011,34(6):983-989.
[5] Bouali M,Ladjal S.A variational approach for the destriping of MODIS data[C]//Proceedings of IEEE International Geoscience and Remote Sensing Symposium.Honolulu:IEEE,2010:2194-2197.
[6] 白磊,姜琦刚,刘万崧,等.近30年来河西走廊湿地变化及其机理初探[J].国土资源遥感,2010,22(1):101-106.doi:10.6046/gtzyyg.2010.01.19"> doi:10.6046/gtzyyg.2010.01.19.
Bai L,Jiang Q G,Liu W S,et al.The change of wetland in Hexi Corridor in the past thirty years and a tentative discussion on its mechanism[J].Remote Sensing for Land and Resources,2010,22(1):101-106.doi:10.6046/gtzyyg.2010.01.19"> doi:10.6046/gtzyyg.2010.01.19.
[7] 孙永军.黄河流域湿地遥感动态监测研究[D].北京:北京大学,2008:24-71.
Sun Y J.Study of Remote Sensing Mornitoring of Wetland Dynamic Change in Yellow River Drainage Area[D].Beijing:Peking University,2008:24-71.
[8] 冯婧.气候变化对黑河流域水资源系统的影响及综合应对[D].上海:东华大学,2014:30-33.
Feng J.Impact of Climate Change on Water Resources System and Coping Strategies in Heihe River Basin[D].Shanghai:Donghua University,2014:30-33.
[9] 熊喆,延晓冬.黑河流域高分辨率区域气候模式建立及其对降水模拟验证[J].科学通报,2014,59(7):605-614.
Xiong Z,Yan X D.Building a high-resolution regional climate model for the Heihe River Basin and simulating precipitation over this region[J].Chinese Science Bulletin,2013,58(36):4670-4678.
[10] 颉耀文,汪桂生.黑河流域历史时期水资源利用空间格局重建[J].地理研究,2014,33(10):1977-1991.
Xie Y W,Wang G S.Reconstruction of historic spatial pattern for water resources utilization in the Heihe River Basin[J].Geographic Research,2014,33(10):1977-1991.
[11] 刘红玉,林振山,王文卿.湿地资源研究进展与发展方向[J].自然资源学报,2009,24(12):2204-2212.
Liu H Y,Lin Z S,Wang W Q.Research progress and development prospect of wetland resources[J].Journal of Nature Resources,2009,24(12):2204-2212.

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