Comparison of the Applicability of J-M Distance Feature Selection Methods for Coastal Wetland Classification DOI Open Access
Xianmei Zhang, Xiaofeng Lin, Dongjie Fu

et al.

Water, Journal Year: 2023, Volume and Issue: 15(12), P. 2212 - 2212

Published: June 12, 2023

Accurate determination of the spatial distribution coastal wetlands is crucial for management and conservation ecosystems. Feature selection methods based on Jeffries-Matusita (J-M) method include J-M distance with simple average ranking (JMave), weights correlations (JMimproved), heuristic (JMmc). However, as impacts these wetland classification are different, their applicability has rarely been investigated. Based Google Earth Engine (GEE) random forest (RF) classifier, this a comparative analysis JMave, JMimproved, JMmc methods. The results show that three compress feature dimensions retain all types much possible. exhibits most significant compression from value 35 to 15 (57.14%), which 37.14% 40% more compressed than JMave respectively. Moreover, they produce comparable results, an overall accuracy 90.20 ± 0.19% Kappa coefficient 88.80 0.22%. different had own advantages land classes. Specifically, better only in cropland, while advantageous recognizing water bodies, tidal flats, aquaculture. While JMimproved failed vegetation mangrove features, it enables depiction mangroves, salt pans, Both rearrange features distance, places emphasis selection. As result, there can be differences subsets among Therefore, further elucidates importance selection, demonstrating potential distance-based classification.

Language: Английский

Mapping and classification of Liao River Delta coastal wetland based on time series and multi-source GaoFen images using stacking ensemble model DOI Creative Commons

Huiya Qian,

Nisha Bao,

Dantong Meng

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 80, P. 102488 - 102488

Published: Jan. 20, 2024

Language: Английский

Citations

19
Dynamic landscapes and the influence of human activities in the Yellow River Delta wetland region DOI Creative Commons
Xinyu Dou, Huadong Guo, Lu Zhang

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 899, P. 166239 - 166239

Published: Aug. 10, 2023

The Yellow River Delta (YRD) wetland is one of the largest and youngest ecosystems in world. It plays an important role regulating climate maintaining ecological balance region. This study analyzes spatiotemporal changes land use, migration, landscape pattern from 2013 to 2022 using Landsat-8 Sentinel-1 data YRD. Then impact human activities are determined by analyzing correlation between socio-economic indicators including nighttime light centroid, total intensity, cultivated area building economic population. results show that increased 1426 km2 during this decade. However, tended be fragmented 2022, with wetlands different types interlacing connectivity decreasing, distribution becoming more concentrated. Different had influences on aspects landscape, expansion mainly compressing core edge, buildings disrupting connectivity, such as intensity centroid causing fragmentation. YRD provide explanation how effect change its which provides available achieve sustainable development goals 6.6 may give access measure human-activity data, could help adject behaviors protect wetlands.

Language: Английский

Citations

31
Vegetation Classification and Evaluation of Yancheng Coastal Wetlands Based on Random Forest Algorithm from Sentinel-2 Images DOI Creative Commons
Yongjun Wang, Shuanggen Jin, Gino Dardanelli

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(7), P. 1124 - 1124

Published: March 22, 2024

The identification of wetland vegetation is essential for environmental protection and management as well monitoring wetlands’ health assessing ecosystem services. However, some limitations on classification may be related to remote sensing technology, confusion between plant species, challenges inadequate data accuracy. In this paper, in the Yancheng Coastal Wetlands studied evaluated from Sentinel-2 images based a random forest algorithm. Based consistent time series observations, characteristic patterns were better captured. Firstly, spectral features, indices, phenological characteristics extracted images, products obtained by constructing dense using dataset Google Earth Engine (GEE). Then, machine learning algorithm obtained, with an overall accuracy 95.64% kappa coefficient 0.94. Four indicators (POP, SOS, NDVIre, B12) main contributors importance weight analysis all features. Comparative experiments conducted different results show that method proposed paper has classification.

Language: Английский

Citations

15
Multi-factor PM2.5 concentration optimization prediction model based on decomposition and integration DOI
Hong Yang,

Wenqian Wang,

Guohui Li

et al.

Urban Climate, Journal Year: 2024, Volume and Issue: 55, P. 101916 - 101916

Published: April 25, 2024

Language: Английский

Citations

13
Stakeholder engagement in advancing sustainable ecotourism: an exploratory case study of Chilika Wetland DOI Creative Commons
Rajashree Samal,

Madhusmita Dash

Discover Sustainability, Journal Year: 2024, Volume and Issue: 5(1)

Published: April 2, 2024

Abstract Ecotourism, over time, has emerged as a preferred strategy for resource utilization within protected areas of developing nations, it effectively bridges the gap between ecological conservation imperatives and imperative local economic development. This study aims to comprehensively analyze multifaceted impacts ecotourism on communities, with due consideration given its environmental, social, dimensions. Furthermore, research endeavors evaluate degree stakeholder engagement in fostering sustainable tourism practices initiatives. Thematic content analysis been used data sourced through field observations, key informant discussions different secondary sources. examines dynamic interaction communities aspects Chilika Wetland India, using DPSIR (Driver-Pressure-State-Impact-Response) framework. It promotes comprehensive decision-making method that considers Triple Bottom Line Community-oriented Collaborative approach. Findings underscore potential Chilika’s ecosystem restoration mitigating adverse tourist effective governance. The need collaboration among stakeholders becomes crucial administration ecotourism, shown by instance Mangalajodi, which exemplifies successful outcome community-led ecotourism. Nevertheless, certain prerequisites, such knowledge dissemination, training, financial support, cultural promotion, eco-friendly infrastructure, commitment conservation, have recognized necessary ensuring long-term community involvement

Language: Английский

Citations

12
Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review DOI Creative Commons
Rosa Maria Cavalli

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(3), P. 446 - 446

Published: Jan. 23, 2024

Since 1971, remote sensing techniques have been used to map and monitor phenomena parameters of the coastal zone. However, updated reviews only considered one phenomenon, parameter, data source, platform, or geographic region. No review has offered an overview that can be accurately mapped monitored with data. This systematic was performed achieve this purpose. A total 15,141 papers published from January 2021 June 2023 were identified. The 1475 most cited screened, 502 eligible included. Web Science Scopus databases searched using all possible combinations between two groups keywords: geographical names in areas platforms. demonstrated that, date, many (103) (39) (e.g., coastline land use cover changes, climate change, urban sprawl). Moreover, authors validated 91% retrieved parameters, 39 1158 times (88% combined together other parameters), 75% over time, 69% several compared results each available products. They obtained 48% different methods, their 17% GIS model techniques. In conclusion, addressed requirements needed more effectively analyze employing integrated approaches: they data, merged

Language: Английский

Citations

11
Assessing urban wetlands dynamics in Wuhan and Nanchang, China DOI
Ying Deng, Zhenfeng Shao, Chaoya Dang

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 901, P. 165777 - 165777

Published: July 29, 2023

Language: Английский

Citations

14
A Study on the Relationship between Urban Spatial Structure Evolution and Ecological Efficiency in Shandong Province DOI Creative Commons
Mingyang Yu, Shuai Xu,

Fangliang Zhou

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(2), P. 818 - 818

Published: Jan. 18, 2024

Strengthening the construction of ecological civilization is an inevitable requirement for promoting high-quality economic and social development. It great significance to study evolutionary trend relationship between urban spatial structure efficiency promote Taking Shandong Province as example, this paper obtains data on factors such points interest, night light, number employed people at end year water supply; uses Anselin Local Moran’s I index identify centers; analyzes distribution form characteristics agglomeration degree space; studies causes differences in based Super-SBM DEA model with undesirable output. The results show that all cities inverse S-shaped circle decreasing trend, Laiwu city has highest compactness (compactness 2.96), Tai ‘an lowest 0.04. level eco-efficiency “low west high east”, difference regions increasing by year. Urban a “first then decreasing” effect eco-efficiency. Technological innovation industrial narrow eco-efficiency, development expands it certain extent. This aims fill gaps existing research. By analyzing evolution resource consumption, will reveal trends changes impact these benefits.

Language: Английский

Citations

4
A phenological knowledge transfer-based fine grained land cover change sample collection method: a case study of coastal wetlands DOI Creative Commons
Linye Zhu, Wenbin Sun, Huaqiao Xing

et al.

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: Jan. 30, 2024

Methods for fine-grained sample collection are essential detecting land cover changes at large scales. The complexity of wetland types increases the difficulty obtaining training samples high-precision changes, while existing methods mainly focus on coarse-grained classification urban areas, ignoring physical growth cycle vegetation. To solve above problems, we propose a method phenological knowledge transfer-based fine grained change (PKT). Taking Yellow River Delta as an example, experimental results shown follows. (1) overall accuracy PKT is 77.03%, and k 0.42, which better than other methods. (2) able to obtain area more accurately can identify type in change. (3) Making full use multisource data category information effectively improve samples. (4) Changes coastal wetlands result interaction between natural factors human activities. (5) Further restoration management be carried out terms appropriate protective measures restrictions construction behavior.

Language: Английский

Citations

4
County-Level Poverty Evaluation Using Machine Learning, Nighttime Light, and Geospatial Data DOI Creative Commons

Xiaoqian Zhang,

Wenjiang Zhang,

Hui Deng

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(6), P. 962 - 962

Published: March 9, 2024

The accurate and timely acquisition of poverty information within a specific region is crucial for formulating effective development policies. Nighttime light (NL) remote sensing data geospatial provide the means conducting precise evaluations levels. However, current assessment methods predominantly rely on NL data, potential combining multi-source identification remains underexplored. Therefore, we propose an approach that assesses based both using machine learning models. This study uses multidimensional index (MPI), derived from county-level statistical with social, economic, environmental dimensions, as indicator to assess We extracted total 17 independent variables data. Machine models (random forest (RF), support vector (SVM), adaptive boosting (AdaBoost), extreme gradient (XGBoost), (LightGBM)) traditional linear regression (LR) were used model relationship between MPI variables. results indicate RF achieved significantly higher accuracy, coefficient determination (R2) 0.928, mean absolute error (MAE) 0.030, root square (RMSE) 0.037. top five most important comprise two (NL_MAX NL_MIN) three (POI_Ed, POI_Me, POI_Ca) geographical spatial highlighting significant roles in modeling. map was generated by depicted detailed distribution Fujian province. presents evaluation integrates model, which can contribute more reliable efficient estimate poverty.

Language: Английский

Citations

4