Four decades of winter wetland changes in Poyang Lake based on Landsat observations between 1973 and 2013

Han, Xingxing; Chen, Xiaoling; Feng, Lian

doi:10.1016/j.rse.2014.10.003

Cited by 230 publications

(138 citation statements)

References 27 publications

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“…Given the connotation of ecosystem health [24], characteristics of Lake Poyang [18,20,25] and previous assessments [8,11,12], natural indicators were divided into three subject areas for measuring physical, chemical, and biological integrity.…”

Section: Metric Selectionmentioning

confidence: 99%

Assessing Aquatic Ecological Health for Lake Poyang, China: Part I Index Development

Huang

Gao

et al. 2018

Water

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Abstract:The development of an ecosystem health index to assess health status in freshwater lakes is urgently needed in China, especially in polluted lakes. This study developed a specific Ecosystem Health Index (LP-EHI) for Lake Poyang in China. LP-EHI quantified lake health from the perspectives of physical, chemical, biological integrity and social service. Physical integrity indices included hydrological conditions (water level and runoff), basic morphometric characteristics (lake area and shoreline), and tributary connectivity. Chemical integrity indices used water quality, nutrition, and toxicity to quantify chemical impairment. Biological integrity indicators covered six major components of the aquatic food chain, namely, phytoplankton, zooplankton, benthic macroinvertebrates, wetland plants, fish, and wintering birds. Social service indices included drinking water, pathogenic potential, flood storage capacity, sand mining, and dish-shaped sub-lake areas under management to measure whether the lake fulfilled the needs of human society. Reference and impaired conditions for each metric were defined by "historical" conditions, "least disturbed" conditions, national standards and expert opinions. The value of LP-EHI ranging from 0 to 1 was divided into five health conditions: excellent (≥0.8), good (0.6-0.8), fair (0.4-0.6), poor (0.2-0.4) and bad (<0.2). The metrics' reliability was further validated using a box-and-whisker plot test. The developed index (LP-EHI) is so far the most comprehensive index to evaluate ecosystem health for Lake Poyang, and is well reflected in the unique characteristics of Lake Poyang. It can enhance our understanding of lake health conditions and thus guide lake management to achieve better health conditions.

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Section: Metric Selectionmentioning

confidence: 99%

Assessing Aquatic Ecological Health for Lake Poyang, China: Part I Index Development

Huang

Gao

et al. 2018

Water

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“…However, the structure and spectral signature of the different wetlands are heterogeneous across space and time [27,29,58]. It is hard to select representative samples at the per-parcel level.…”

Section: Wetland Automatic Classification and Updating Via Transfer Lmentioning

confidence: 99%

Four Decades of Estuarine Wetland Changes in the Yellow River Delta Based on Landsat Observations Between 1973 and 2013

Zhu

Zhang

Huang

2018

Water

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Yellow River Delta wetlands are essential for the migration of endangered birds and breeding. The wetlands, however, have been severely damaged during recent decades, partly due to the lack of wetland ecosystem protection by authorities. To have a better historical understanding of the spatio-temporal dynamics of the wetlands, this study aims to map and characterize patterns of the loss and degradation of wetlands in the Yellow River Delta using a time series of remotely sensed images (at nine points in time) based on object-based image analysis and knowledge transfer learning technology. Spatio-temporal analysis was conducted to document the long-term changes taking place in different wetlands over the four decades. The results showed that the Yellow River Delta wetlands have experienced significant changes between 1973 and 2013. The total area of wetlands has been reduced by 683.12 km 2 during the overall period and the trend of loss continues. However, the rates and trends of change for the different types of wetlands were not the same. The natural wetlands showed a statistically significant decrease in area during the overall period (36.04 km 2 ·year −1 ). Meanwhile, the artificial wetlands had the opposite trend and showed a statistically significant increase in area during the past four decades (18.96 km 2 ·year −1 ). According to the change characteristics revealed by the time series wetland classification maps, the evolution process of the Yellow River Delta wetlands could be divided into three stages: (1) From 1973From -1984, basically stable, but with little increase; (2) from 1984-1995, rapid loss; and (3) from 1995-2013, slow loss. The area of the wetlands reached a low point around 1995, and then with a little improvement, the regional wetlands entered a slow loss stage. It is believed that interference by human activities (e.g., urban construction, cropland creation, and oil exploitation) was the main reason for wetland degradation in the Yellow River Delta over the past four decades. Climate change also has long-term impacts on regional wetlands. In addition, due to the special geographical environment, the hydrological and sediment conditions and the location of the Yellow River mouth also have a significant influence on the evolution process of the wetlands.

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“…In the random forest model, the number of classification trees (T) and the number of features (m) at each node for spilling, is critical to the results [36]. This study employed an RF classifier with 5,10,15,20,25,30,35,40,45, and 50 classification trees and chose the optimal item based on the OOB accuracy, using water and non-water samples as the input data. Our sensitivity tests indicate that 20 classification trees are best because, beyond that, the classification gains little performance improvement.…”

Section: Image Classification Based On Random Forest Modelmentioning

confidence: 99%

“…Remote-sensing data have been widely used for mapping the lake-water extent over time and space [10][11][12][13][14][15][16][17], with Landsat image data being one of the most common data types for monitoring and analyzing long-term lake-water extent changes, due to their high spatial resolution (30-60 m) and long data record [11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Change of Lake Water Extent in Wuhan Urban Agglomeration Based on Landsat Images from 1987 to 2015

et al. 2017

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Abstract:Urban lakes play an important role in urban development and environmental protection for the Wuhan urban agglomeration. Under the impacts of urbanization and climate change, understanding urban lake-water extent dynamics is significant. However, few studies on the lake-water extent changes for the Wuhan urban agglomeration exist. This research employed 1375 seasonally continuous Landsat TM/ETM+/OLI data scenes to evaluate the lake-water extent changes from 1987 to 2015. The random forest model was used to extract water bodies based on eleven feature variables, including six remote-sensing spectral bands and five spectral indices. An accuracy assessment yielded a mean classification accuracy of 93.11%, with a standard deviation of 2.26%. The calculated results revealed the following: (1) The average maximum lake-water area of the Wuhan urban agglomeration was 2262.17 km 2 from 1987 to 2002, and it decreased to 2020.78 km 2 from 2005 to 2015, with a loss of 241.39 km 2 (10.67%). (2) The lake-water areas of loss of Wuhan, Huanggang, Xianning, and Xiaogan cities, were 114.83 km 2 , 44.40 km 2 , 45.39 km 2 , and 31.18 km 2 , respectively, with percentages of loss of 14.30%, 11.83%, 13.16%, and 23.05%, respectively. (3) The lake-water areas in the Wuhan urban agglomeration were 226.29 km 2 , 322.71 km 2 , 460.35 km 2 , 400.79 km 2 , 535.51 km 2 , and 635.42 km 2 under water inundation frequencies of 5%-10%, 10%-20%, 20%-40%, 40%-60%, 60%-80%, and 80%-100%, respectively. The Wuhan urban agglomeration was approved as the pilot area for national comprehensive reform, for promoting resource-saving and environmentally friendly developments. This study could be used as guidance for lake protection and water resource management.

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Four decades of winter wetland changes in Poyang Lake based on Landsat observations between 1973 and 2013

Cited by 230 publications

References 27 publications

Assessing Aquatic Ecological Health for Lake Poyang, China: Part I Index Development

Assessing Aquatic Ecological Health for Lake Poyang, China: Part I Index Development

Four Decades of Estuarine Wetland Changes in the Yellow River Delta Based on Landsat Observations Between 1973 and 2013

Spatio-Temporal Change of Lake Water Extent in Wuhan Urban Agglomeration Based on Landsat Images from 1987 to 2015

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