PMID- 38154774
OWN - NLM
STAT- MEDLINE
DCOM- 20240214
LR  - 20240214
IS  - 1873-6424 (Electronic)
IS  - 0269-7491 (Linking)
VI  - 343
DP  - 2024 Feb 15
TI  - Extraction of eutrophic and green ponds from segmentation of high-resolution 
      imagery based on the EAF-Unet algorithm.
PG  - 123207
LID - S0269-7491(23)02209-1 [pii]
LID - 10.1016/j.envpol.2023.123207 [doi]
AB  - Inland ponds exhibit remarkable ubiquity across the globe, playing a vital role 
      in the sustainability of global continental freshwater resources and contributing 
      significantly to their biodiversity. Numerous ponds are eutrophic and experience 
      recurrent seasonal or year-round algal blooms or persistent duckweed cover, 
      conferring a characteristic green hue. Here, we denote these eutrophic and green 
      ponds as EGPs. The excessive proliferation of algal blooms and duckweed within 
      these EGPs poses a significant threat to the ecological functioning of these 
      aquatic systems, which can lead to hypoxia or the release of microcystins. To 
      identify these EGPs automatically, we constructed an Efficient Attention Fusion 
      Unet (EAF-Unet) algorithm using Gaofen-2 (GF2) panchromatic and multispectral 
      imagery. The attention mechanism was incorporated in Unet to help better detect 
      EGPs. Using the first EGP labeled dataset, we determined the best input feature 
      combination (RGB, NIR, NDVI, and Bright) and the most effective encoding 
      (Rasnet50) for EAF-Unet for distinguishing EGPs from other ground cover types. 
      The evaluation indices - Precision (0.81), Recall (0.79), F1-Score (0.80), and 
      Intersection over Union (IoU, 0.67) - indicate that EAF-Unet can accurately and 
      robustly extract EGPs from GF2 images without relying on pond water masks. 
      Remote-sensing EGP products can assist in identifying ponds with severe 
      eutrophication. Moreover, these products can serve as references for identifying 
      high-risk areas prone to improper sewage discharge or inadequate sewer 
      construction.
CI  - Copyright (c) 2023. Published by Elsevier Ltd.
FAU - Hu, Yating
AU  - Hu Y
AD  - College of Information Technology, Jilin Agricultural University, Changchun, 
      130118, China.
FAU - Zheng, Danyang
AU  - Zheng D
AD  - College of Information Technology, Jilin Agricultural University, Changchun, 
      130118, China.
FAU - Shi, Shuqiong
AU  - Shi S
AD  - Ministry of Ecology and Environment of China, Beijing, 100029, China.
FAU - Wang, Yu
AU  - Wang Y
AD  - Center for Satellite Application on Ecology and Environment, Ministry of Ecology 
      and Environment of the People's Republic of China, Beijing, 100029, China.
FAU - Liu, Ge
AU  - Liu G
AD  - Northeast Institute of Geography and Agroecology, CAS, Changchun, 130102, China. 
      Electronic address: liugers@163.com.
FAU - Song, Kaishan
AU  - Song K
AD  - Northeast Institute of Geography and Agroecology, CAS, Changchun, 130102, China.
FAU - Mao, Dehua
AU  - Mao D
AD  - Northeast Institute of Geography and Agroecology, CAS, Changchun, 130102, China.
FAU - Wu, Shihong
AU  - Wu S
AD  - Tianjin Research Institute for Water Transport Engineering, State Ministry of 
      Transport, Tianjin, 300456, China.
FAU - Tian, Liqiao
AU  - Tian L
AD  - State Key Laboratory of Information Engineering in Surveying, Mapping and Remote 
      Sensing, Wuhan University, Wuhan, 430079, China.
LA  - eng
PT  - Journal Article
DEP - 20231227
PL  - England
TA  - Environ Pollut
JT  - Environmental pollution (Barking, Essex : 1987)
JID - 8804476
RN  - 27YLU75U4W (Phosphorus)
SB  - IM
MH  - *Ponds
MH  - *Fresh Water
MH  - Eutrophication
MH  - Phosphorus
OTO - NOTNLM
OT  - Attention mechanism
OT  - Bright index
OT  - EAF-Unet network
OT  - Eutrophic and green ponds
OT  - GF2 images
OT  - Rasnet50
COIS- Declaration of competing interest The authors declare that they have no known 
      competing financial interests or personal relationships that could have appeared 
      to influence the work reported in this paper.
EDAT- 2023/12/29 00:42
MHDA- 2024/02/10 22:54
CRDT- 2023/12/28 19:29
PHST- 2023/10/05 00:00 [received]
PHST- 2023/11/25 00:00 [revised]
PHST- 2023/12/20 00:00 [accepted]
PHST- 2024/02/10 22:54 [medline]
PHST- 2023/12/29 00:42 [pubmed]
PHST- 2023/12/28 19:29 [entrez]
AID - S0269-7491(23)02209-1 [pii]
AID - 10.1016/j.envpol.2023.123207 [doi]
PST - ppublish
SO  - Environ Pollut. 2024 Feb 15;343:123207. doi: 10.1016/j.envpol.2023.123207. Epub 
      2023 Dec 27.