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Remote Sensing
Volume 13
Issue 3
10.3390/rs13030443
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Article

A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine

by
Nan Wu
1,2,3,
Runhe Shi
1,2,3,4,*,
Wei Zhuo
1,2,3,
Chao Zhang
1,2,3,
Bingchan Zhou
1,2,3,
Zilong Xia
2,
Zhu Tao
1,2,3,
Wei Gao
5 and
Bo Tian
6
1
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
2
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
3
Joint Laboratory for Environmental Remote Sensing and Data Assimilation, East China Normal University, Shanghai 200241, China
4
Institute of Eco-Chongming, East China Normal University, Shanghai 200241, China
5
Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80523, USA
6
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(3), 443; https://doi.org/10.3390/rs13030443
Submission received: 19 December 2020 / Revised: 20 January 2021 / Accepted: 25 January 2021 / Published: 27 January 2021
(This article belongs to the Collection Google Earth Engine Applications)
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Abstract

The composition and distribution of wetland vegetation is critical for ecosystem diversity and sustainable development. However, tidal flat wetland environments are complex, and obtaining effective satellite imagery is challenging due to the high cloud coverage. Moreover, it is difficult to acquire phenological feature data and extract species-level wetland vegetation information by using only spectral data or individual images. To solve these limitations, statistical features, temporal features, and phenological features of multiple Landsat 8 time-series images obtained via the Google Earth Engine (GEE) platform were compared to extract species-level wetland vegetation information from Chongming Island, China. The results indicated that (1) a harmonic model obtained the phenological characteristics of wetland vegetation better than the raw vegetation index (VI) and the Savitzky–Golay (SG) smoothing method; (2) classification based on the combination of the three features provided the highest overall accuracy (85.54%), and the phenological features (represented by the amplitude and phase of the harmonic model) had the greatest impact on the classification; and (3) the classification result from the senescence period was more accurate than that from the green period, but the annual mapping result on all seasons was the most accurate. The method described in this study can be applied to overcome the impacts of the complex environment in tidal flat wetlands and to effectively classify wetland vegetation species using GEE. This study could be used as a reference for the analysis of the phenological features of other areas or vegetation types.
Keywords: tidal flat vegetation classification; Google Earth Engine; harmonic model; phenological features; Chongming Island tidal flat vegetation classification; Google Earth Engine; harmonic model; phenological features; Chongming Island
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MDPI and ACS Style

Wu, N.; Shi, R.; Zhuo, W.; Zhang, C.; Zhou, B.; Xia, Z.; Tao, Z.; Gao, W.; Tian, B. A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine. Remote Sens. 2021, 13, 443. https://doi.org/10.3390/rs13030443

AMA Style

Wu N, Shi R, Zhuo W, Zhang C, Zhou B, Xia Z, Tao Z, Gao W, Tian B. A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine. Remote Sensing. 2021; 13(3):443. https://doi.org/10.3390/rs13030443

Chicago/Turabian Style

Wu, Nan, Runhe Shi, Wei Zhuo, Chao Zhang, Bingchan Zhou, Zilong Xia, Zhu Tao, Wei Gao, and Bo Tian. 2021. "A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine" Remote Sensing 13, no. 3: 443. https://doi.org/10.3390/rs13030443

APA Style

Wu, N., Shi, R., Zhuo, W., Zhang, C., Zhou, B., Xia, Z., Tao, Z., Gao, W., & Tian, B. (2021). A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine. Remote Sensing, 13(3), 443. https://doi.org/10.3390/rs13030443

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