Dataset List

Vol.|Area

Data Details

Spatial-temporal Dataset of Tidal Creek Morphological Characteristics in Yellow River Delta (1998-2018)


MOU Kuinan1,2GONG Zhaoning*1,2QIU Huachang1,2
1 College of Resource Environment and Tourism,Capital Normal University,Beijing 100048,China2 MCA Key Laboratory of Disaster Assessment and Risk Prevention,Capital Normal University,Beijing 100048,China

DOI:10.3974/geodb.2022.01.09.V1

Published:Jan. 2022

Visitors:1308       Data Files Downloaded:37      
Data Downloaded:550.16 MB      Citations:

Key Words:

tidal creek,morphological characteristics,spatial-temporal,Yellow River Delta,1998-2018

Abstract:

The tidal creek is the main channel for the interaction of the land-sea ecosystem. The morphological characteristics of tidal creeks have obvious temporal and spatial heterogeneity. Based on the Landsat TM/OLI satellite data of 20 scenes covering Yellow River Delta from 1998 to 2018 (cloud cover <10%), the tidal creeks of the study area were extracted using the accurate extraction algorithm of the tidal creek network in the heterogeneous background. After the tidal creeks were classified by the fast automatic classification algorithm of tidal creeks, the GIS spatial analysis function was used to extract the morphological characteristic parameters of the tidal creeks in the five-year study area, and the spatial-temporal dataset of tidal creek morphological characteristics in Yellow River Delta (1998-2018) was developed. The dataset is consisted of the following data: (1) the maximum extent of tidal flats; (2) spatial tidal creeks; (3) kernel density of tidal creek density; (4) kernel density of tidal creek bifurcation ratio; (5) over marsh path length data. Among them, the spatial resolution of the raster data is 30 m. The projection is WGS_1984_UTM_Zone_50N. The dataset is archived in .shp and .tif data formats, and consists of 120 data files with data size of 81.4 MB (compressed to 1 file with 14.8 MB). The analysis paper based on this dataset was published in Acta Geographica Sinica, Vol. 76, No. 9, 2021.

Foundation Item:

Ministry of Science and Technology of P. R. China (2017YFC0505903); National Natural Science Foundation of China (41971381)

Data Citation:

MOU Kuinan, GONG Zhaoning*, QIU Huachang. Spatial-temporal Dataset of Tidal Creek Morphological Characteristics in Yellow River Delta (1998-2018)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.01.09.V1.

References:

[1] Wang, Q. W., Gong, Z. N., Guan, H. L., et al. Extracting method of tidal creek features under heterogeneous background at Yellow River Delta using remotely sensed imaggery. Chinese Journal of Applied Ecology, 2019, 30(9): 3097-3107.
     [2] Gong, Z. N., Wang, Q. W., Guan, H. L., et al. Extracting tidal creek features in a heterogeneous background using Sentinel-2 im-agery: a case study in the Yellow River Delta, China [J]. International Journal of Remote Sensing, 2020, 41(10): 3653-3676.
     [3] Wu, Y. N., Wang, Y., Zhang, Z. M. Effects of tidal creek morphology on succession of wetland plant communities in the Yellow River Delta. Ecological Science, 2020, 39(1): 33-41.
     [4] Marani, M., Belluco, E., D'Alpaos, A., et al. On the drainage density of tidal networks [J]. Water Resources Research, 2003, 39(2): 1040.
     [5] Horton, R. E., Htrata, T. Erosional development of streams and their drainage basins, hydrophyrical approach to quan-titative morphology [J]. Journal of the Japanese Forest Society, 1955, 37(6): 257-262.
     [6] Chirol, C., Haigh, I. D., Pontee, N., et al. Parametrizing tidal creek morphology in mature saltmarshes using semi-automated extraction from lidar [J]. Remote Sensing of Environment, 2018, 209: 291-311.
     [7] Lohani, B., Mason, D. C., Scott, T. R., et al. Extraction of tidal channel networks from aerial photographs alone and com-bined with laser altimetry [J]. International Journal of Remote Sensing, 2006, 27(1): 5-25.
     

Data Product:

ID Data Name Data Size Operation
1 TidalCreekYRD_1998-2018.rar 15226.02KB
Co-Sponsors
Superintend