Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China

Ma Wei; Zhang Yangwu; Zhou Tianyuan; Jiang Yafang; Liu Zengli

doi:doi:10.11648/j.earth.20211006.15

| Peer-Reviewed

Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China

Ma Wei, Zhang Yangwu, Zhou Tianyuan, Jiang Yafang, Liu Zengli

Published in Earth Sciences (Volume 10, Issue 6)

Received: 25 October 2021 Accepted: 15 November 2021 Published: 17 November 2021

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Investigation and monitoring of wetland is an important and fundamental work. Wetland area estimation by systematic sampling would have higher precision than that get by traditional random sampling. In this paper, wetland areas of different types in Ningxia were estimated by spacial sampling method, based on remote sensing data from 2015 to 2016. Results showed that: 1) According to the second national wetland resource inventory database, wetland area in Ningxia was 20.72×10⁴ hm², which decreased gradually from north to south, and Wuzhong had relatively largest areas of lakes and marsh wetland. 2) Based with 210 of 4 km×4 km quadrat sampling grids, estimation of wetland area in Ningxia was 21.70×10⁴ hm², with estimation accuracy of 94.53% and sampling accuracy of 99.78%, which was reliability but the sampling accuracy would decline with the proportion decrease of sampling wetland area. 3) Based with 61 of 4 km×4 km quadrat sampling grids, wetland area in Wuzhong was estimated as 52320.67 hm² with estimation accuracy of 98.58%, occurred in a net increase of 731.78 hm² from 2013 to 2016. In conclusion, the spacial sampling method proposed in this research for wetland resource inventory and dynamic monitoring is available and worth of spreading within certain realms, which would improve the protection, management, restoration and sustainable development for wetland resource.

Published in	Earth Sciences (Volume 10, Issue 6)
DOI	10.11648/j.earth.20211006.15
Page(s)	292-297
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Wetland Area, Spacial Sampling, Sampling Grids, Estimation Accuracy, Dynamic Monitoring

References

[1]	Liu Ping, Guan Lei, Lv Cai. et al, Technical Characteristics and Application Prospects of Achievements of the Second National Wetland Investigation, WETLAND SCIENCE, 3rd ed., vol. 9, 2011, pp. 284-289.
[2]	Liu Zigang, Ma Xuehui, Overview of Wetlands in China, BeiJing: China Forestry Publishing House, 2008.
[3]	Ma Guangren, China Wetlands Resources Master Volume, BeiJing: China Forestry Publishing House, 2015.
[4]	State Forestry Administration, Technical Regulations for National Wetland Resources Survey (Trial), BeiJing: China Forestry Publishing House, 2008.
[5]	Li Lianfa, Wang Jinfeng, Liu Jiyuan, Optimal Decision of Spatial Sampling in Land and Remote Sensing Survey, Science In China Ser. D Earth Sciences, 10rd ed., vol. 34, 2004, pp. 975-982.
[6]	Zhu Shuang, Zhang Jinshui, Provincial agricultural stratification method for crop area estimation by remote sensing, Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2rd ed., vol. 29, 2013, pp. 184-191.
[7]	Wang Di, Zhou Qingbo, Chen Zhongxin, et al, Optimization of spatial sampling schemes for maize planting acreage estimation, Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 8rd ed., vol. 30, 2014, pp. 117-125.
[8]	Zhang Xiaowei, She Guanghui, Wen Xiaorong, et al, The application of spatial stratified sampling in remote sensing monitoring of forest cover, Journal of Nanjing Forestry University (Natural Science Edition), 3rd ed., vol. 36, 2012, pp. 81-84.
[9]	Zhou Xinwei, Gong Huili, Zhao Wenji, et al, Dynamic Monitoring and Analysis of Wetland Resources in Beijing, ACTA GEOGRAPHICA SINICA, 61 (6), 2006, pp. 654-662.
[10]	Peng Jian, Wang Guangsheng, Wang Menghe, et al, Distribution and Change of Wetlands in Anhui Province in 3 Periods, WETLAND SCIENCE, 1rd ed., vol. 15, 2017, pp. 47-51.
[11]	Chen Lin, Ren Chunying, Wang Can, et al, Dynamic of Coastal Wetlands of the Yellow River Delta for 6 Periods, WETLAND SCIENCE, 2rd ed., vol. 15, 2017, pp. 179-186.
[12]	Ma Xueyao, Du Jia, Liang Yuhua, et al, Changes of Coastal Wetlands in the Yangtze River Delta for 6 Periods since 1960s and Their Driving Factors, WETLAND SCIENCE, 3rd ed., vol. 16, 2018, pp. 303-312.
[13]	Zhao wei, Remote Sensing Monitoring of Wetland Protection Project and Sampling System Construction—Take the Protection Project of Xixi Wetland in Hangzhou as an Example, Hangzhou: Zhejiang A&F University, 2010.
[14]	Li Tianxiang, Gong Jianzhou, Cui Haishan, et al, Remote sensing classification for wetlands in Nansha district of Guangzhou based on stratified sampling, Journal of Guangzhou University (Natural Science Edition), 4rd ed., vol. 15, 2016, pp. 89-95.
[15]	Zhang Dingxiang, Chen Honglei, Ji Hongwei, et al, National Grating Data Production Methods of Land Use, Land and resources informatization, 2rd ed., 2014, pp. 32-39.
[16]	Wang Haibin, Deng Huafeng, Cheng Zhichu, et al, Study on forest vegetation area spatial sampling method based on 3S, Journal of Forest and Environment, 2015, 1rd ed., vol. 35, pp. 74-80.
[17]	Wang Xuejun; Ma Wei; Huang Guo-sheng, et al, Estimation of forest area by large plot interpretation and division based on remote sensing, Journal of Beijing Forestry University, 17rd ed., vol. 37, 2015, pp. 1-9.
[18]	Ernst T L, Leibowitz N C, Roose D, et al, Evaluation of US EPS environmental monitoring and assessment program’s wetlands sampling design and classification, Environmental Management, 1rd ed., vol. 19, 1995, pp. 99-113.
[19]	Guo Hongling, “China Wetlands Resources Ningxia Volume, Beijing: China Forestry Publishing House, 2015.
[20]	You Xianxiang, “Principles of Remote Sensing and Its Application in Resources and Environment, Beijing: China Forestry Publishing House, 2003, pp. 34-39.
[21]	Feng Yiming, Tang Shouzheng, Li Zengyuan, Application of Spatial Statistic Analysis in Forestry, SCIENTIA SILVAE SINICAE, 3rd ed., vol. 40, 2004, pp. 149-155.
[22]	Zeng Weisheng, Cheng Zhichu, Xia Chaozong, A New Scheme for Coordinating Continuous Forest Inventory with Forest Management Inventory, CENTRAL SOUTH FOREST INVENTORY AND PLANNING, 3rd ed., vol. 31, 2012, pp. 1-4.
[23]	Wang huanping, Study on Remotely Sensed Monitoring of Wetland at Zhongwei Oasis and Its Adjacent Regions, Lanzhou: Lanzhou University, 2012.
[24]	Zhao Hui, Zhang Haiying, Li Na na, et al, RS-Based Research of Chinese Wetland: Status and Trend, Geography and Geo-Information Science, 2rd ed., vol. 26, 2010, pp. 62-66.
[25]	Sun Yongjun, Study of Remote Sensing Mornitoring of Wetland Dynamic Chang in Yellow River Drainage Area, Beijing: Beijing University, 2008.
[26]	Mo Wenchao, Study on remote sensing monitoring and landscape patterm dynamics of Quanzhou Bay coastal wetland during the past 20 years, Fuzhou: pp. Fujian Agriculture and Forestry University, 2017.
[27]	Niu Z, Zhang H, Wang X, et al, Mapping wetland changes in China between 1978 and 2008, Chinese Science Bulletin, 57rd ed., vol. 22, 2012, pp. 2813-2823.
[28]	Whigham D F, Weller D E, Jacobs A D, et al, Assessing the ecological condition of wetlands at the catchment scale, Landscape, 2rd ed., 2003, pp. 99-112.
[29]	Zhang Shuwen, Yan Fengqin, Yu Lingxue, et al, Application of Remote Sensing Technology to Wetland Research, SCIENTIA GEOGRAPHICA SINICA, 11rd ed., vol. 33, 2013, pp. 1406-1412.
[30]	Liu Runhong, Liang Shichu, Zhaohongyan. et al, Progress of Chinese Coastal Wetland based on Remote Sensing, Remote Sensing Technology and Application, 6rd ed., vol. 32, 2017, pp. 998-1011.

Cite This Article

Plain Text BibTeX RIS

APA Style

Ma Wei, Zhang Yangwu, Zhou Tianyuan, Jiang Yafang, Liu Zengli. (2021). Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China. Earth Sciences, 10(6), 292-297. https://doi.org/10.11648/j.earth.20211006.15

Copy | Download

ACS Style

Ma Wei; Zhang Yangwu; Zhou Tianyuan; Jiang Yafang; Liu Zengli. Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China. Earth Sci. 2021, 10(6), 292-297. doi: 10.11648/j.earth.20211006.15

Copy | Download

AMA Style

Ma Wei, Zhang Yangwu, Zhou Tianyuan, Jiang Yafang, Liu Zengli. Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China. Earth Sci. 2021;10(6):292-297. doi: 10.11648/j.earth.20211006.15

Copy | Download

@article{10.11648/j.earth.20211006.15,
  author = {Ma Wei and Zhang Yangwu and Zhou Tianyuan and Jiang Yafang and Liu Zengli},
  title = {Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China},
  journal = {Earth Sciences},
  volume = {10},
  number = {6},
  pages = {292-297},
  doi = {10.11648/j.earth.20211006.15},
  url = {https://doi.org/10.11648/j.earth.20211006.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20211006.15},
  abstract = {Investigation and monitoring of wetland is an important and fundamental work. Wetland area estimation by systematic sampling would have higher precision than that get by traditional random sampling. In this paper, wetland areas of different types in Ningxia were estimated by spacial sampling method, based on remote sensing data from 2015 to 2016. Results showed that: 1) According to the second national wetland resource inventory database, wetland area in Ningxia was 20.72×104 hm2, which decreased gradually from north to south, and Wuzhong had relatively largest areas of lakes and marsh wetland. 2) Based with 210 of 4 km×4 km quadrat sampling grids, estimation of wetland area in Ningxia was 21.70×104 hm2, with estimation accuracy of 94.53% and sampling accuracy of 99.78%, which was reliability but the sampling accuracy would decline with the proportion decrease of sampling wetland area. 3) Based with 61 of 4 km×4 km quadrat sampling grids, wetland area in Wuzhong was estimated as 52320.67 hm2 with estimation accuracy of 98.58%, occurred in a net increase of 731.78 hm2 from 2013 to 2016. In conclusion, the spacial sampling method proposed in this research for wetland resource inventory and dynamic monitoring is available and worth of spreading within certain realms, which would improve the protection, management, restoration and sustainable development for wetland resource.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China
AU  - Ma Wei
AU  - Zhang Yangwu
AU  - Zhou Tianyuan
AU  - Jiang Yafang
AU  - Liu Zengli
Y1  - 2021/11/17
PY  - 2021
N1  - https://doi.org/10.11648/j.earth.20211006.15
DO  - 10.11648/j.earth.20211006.15
T2  - Earth Sciences
JF  - Earth Sciences
JO  - Earth Sciences
SP  - 292
EP  - 297
PB  - Science Publishing Group
SN  - 2328-5982
UR  - https://doi.org/10.11648/j.earth.20211006.15
AB  - Investigation and monitoring of wetland is an important and fundamental work. Wetland area estimation by systematic sampling would have higher precision than that get by traditional random sampling. In this paper, wetland areas of different types in Ningxia were estimated by spacial sampling method, based on remote sensing data from 2015 to 2016. Results showed that: 1) According to the second national wetland resource inventory database, wetland area in Ningxia was 20.72×104 hm2, which decreased gradually from north to south, and Wuzhong had relatively largest areas of lakes and marsh wetland. 2) Based with 210 of 4 km×4 km quadrat sampling grids, estimation of wetland area in Ningxia was 21.70×104 hm2, with estimation accuracy of 94.53% and sampling accuracy of 99.78%, which was reliability but the sampling accuracy would decline with the proportion decrease of sampling wetland area. 3) Based with 61 of 4 km×4 km quadrat sampling grids, wetland area in Wuzhong was estimated as 52320.67 hm2 with estimation accuracy of 98.58%, occurred in a net increase of 731.78 hm2 from 2013 to 2016. In conclusion, the spacial sampling method proposed in this research for wetland resource inventory and dynamic monitoring is available and worth of spreading within certain realms, which would improve the protection, management, restoration and sustainable development for wetland resource.
VL  - 10
IS  - 6
ER  -

Copy | Download

Author Information

Ma Wei

Academy of Forest Inventory and Planning, National Forestry and Grassland Administration, Beijing, China
Zhang Yangwu

Department of Natural Resources Investigation and Monitoring, Ministry of Natural Resources, Beijing, China
Zhou Tianyuan

Academy of Forest Inventory and Planning, National Forestry and Grassland Administration, Beijing, China
Jiang Yafang

Academy of Forest Inventory and Planning, National Forestry and Grassland Administration, Beijing, China
Liu Zengli

Academy of Forest Inventory and Planning, National Forestry and Grassland Administration, Beijing, China

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Ma Wei, Zhang Yangwu, Zhou Tianyuan, Jiang Yafang, Liu Zengli. (2021). Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China. Earth Sciences, 10(6), 292-297. https://doi.org/10.11648/j.earth.20211006.15

Copy | Download

ACS Style

Ma Wei; Zhang Yangwu; Zhou Tianyuan; Jiang Yafang; Liu Zengli. Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China. Earth Sci. 2021, 10(6), 292-297. doi: 10.11648/j.earth.20211006.15

Copy | Download

AMA Style

Ma Wei, Zhang Yangwu, Zhou Tianyuan, Jiang Yafang, Liu Zengli. Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China. Earth Sci. 2021;10(6):292-297. doi: 10.11648/j.earth.20211006.15

Copy | Download

@article{10.11648/j.earth.20211006.15,
  author = {Ma Wei and Zhang Yangwu and Zhou Tianyuan and Jiang Yafang and Liu Zengli},
  title = {Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China},
  journal = {Earth Sciences},
  volume = {10},
  number = {6},
  pages = {292-297},
  doi = {10.11648/j.earth.20211006.15},
  url = {https://doi.org/10.11648/j.earth.20211006.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20211006.15},
  abstract = {Investigation and monitoring of wetland is an important and fundamental work. Wetland area estimation by systematic sampling would have higher precision than that get by traditional random sampling. In this paper, wetland areas of different types in Ningxia were estimated by spacial sampling method, based on remote sensing data from 2015 to 2016. Results showed that: 1) According to the second national wetland resource inventory database, wetland area in Ningxia was 20.72×104 hm2, which decreased gradually from north to south, and Wuzhong had relatively largest areas of lakes and marsh wetland. 2) Based with 210 of 4 km×4 km quadrat sampling grids, estimation of wetland area in Ningxia was 21.70×104 hm2, with estimation accuracy of 94.53% and sampling accuracy of 99.78%, which was reliability but the sampling accuracy would decline with the proportion decrease of sampling wetland area. 3) Based with 61 of 4 km×4 km quadrat sampling grids, wetland area in Wuzhong was estimated as 52320.67 hm2 with estimation accuracy of 98.58%, occurred in a net increase of 731.78 hm2 from 2013 to 2016. In conclusion, the spacial sampling method proposed in this research for wetland resource inventory and dynamic monitoring is available and worth of spreading within certain realms, which would improve the protection, management, restoration and sustainable development for wetland resource.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Research on Estimation of Wetland Area Based on Spacial Sampling Method-A Case Study of Ningxia Hui Autonomous Region in China
AU  - Ma Wei
AU  - Zhang Yangwu
AU  - Zhou Tianyuan
AU  - Jiang Yafang
AU  - Liu Zengli
Y1  - 2021/11/17
PY  - 2021
N1  - https://doi.org/10.11648/j.earth.20211006.15
DO  - 10.11648/j.earth.20211006.15
T2  - Earth Sciences
JF  - Earth Sciences
JO  - Earth Sciences
SP  - 292
EP  - 297
PB  - Science Publishing Group
SN  - 2328-5982
UR  - https://doi.org/10.11648/j.earth.20211006.15
AB  - Investigation and monitoring of wetland is an important and fundamental work. Wetland area estimation by systematic sampling would have higher precision than that get by traditional random sampling. In this paper, wetland areas of different types in Ningxia were estimated by spacial sampling method, based on remote sensing data from 2015 to 2016. Results showed that: 1) According to the second national wetland resource inventory database, wetland area in Ningxia was 20.72×104 hm2, which decreased gradually from north to south, and Wuzhong had relatively largest areas of lakes and marsh wetland. 2) Based with 210 of 4 km×4 km quadrat sampling grids, estimation of wetland area in Ningxia was 21.70×104 hm2, with estimation accuracy of 94.53% and sampling accuracy of 99.78%, which was reliability but the sampling accuracy would decline with the proportion decrease of sampling wetland area. 3) Based with 61 of 4 km×4 km quadrat sampling grids, wetland area in Wuzhong was estimated as 52320.67 hm2 with estimation accuracy of 98.58%, occurred in a net increase of 731.78 hm2 from 2013 to 2016. In conclusion, the spacial sampling method proposed in this research for wetland resource inventory and dynamic monitoring is available and worth of spreading within certain realms, which would improve the protection, management, restoration and sustainable development for wetland resource.
VL  - 10
IS  - 6
ER  -

Copy | Download