Detailed wetland-type classification using Landsat-8 time-series images: a pixel- and object-based algorithm with knowledge (POK)

GIScience & Remote Sensing, Journal Year: 2023, Volume and Issue: 61(1)

Published: Dec. 15, 2023

Mapping detailed wetland types can offer useful information for management and protection, which strongly support the Global Biodiversity Framework. Many studies have conducted classification at regional, national, global scale, whereas fine-resolution mapping with is still challenging. To address this issue, we developed an integration of pixel- object-based algorithms knowledge (POK) by combining pixel-based random forest hierarchical decision tree. Taking Guangxi Beibu Gulf Economic Zone (GBGEZ) Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as our study areas, produced maps 10 6 non-wetland using Landsat-8 time series. In addition, to comprehensively evaluate accuracy classification, implemented validation based on test samples data inter-comparison existing datasets, respectively. The results indicate that overall map was 91.6% ±1.2%. For types, agricultural pond, coastal shallow water, floodplain, mangrove, reservoir, river, tidal flat achieved good accuracies, both user producer exceeding 88.0%. most accuracies were greater than 72.0%. By comparison it found had consistencies China Ecosystem-type Classification Dataset (CECD) land use dataset, MC_LASAC mangrove Tidal Wetlands in East Asia (TWEA) dataset. 2020, area 4,198.8 km2 GBGEZ 10,932.2 GBA. main two urban agglomerations ponds, waters, mangroves, reservoirs, rivers, flats. Our successfully mapped GBA, serving Framework Convention Biological Diversity.

Language: Английский

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Riverine wetland dynamics and health assessment: A case study in the urban agglomerations along the Yellow River in China’s Ningxia Hui Autonomous Region

Ecological Indicators, Journal Year: 2024, Volume and Issue: 162, P. 111965 - 111965

Published: April 12, 2024

Riverine wetland is one of the important cityscapes along rivers, featuring powerful eco-hydrological regulations in safeguarding urban security and serving its quality. Over past several decades, intensified climate change, together with upgraded human activities, have deeply disturbed riverine worldwide caused variations amount pattern, which might lead to negative effects on ecosystem health (WEH), thus threaten sustainability agglomerations. To better understand mechanism above effectiveness, Urban Agglomerations Yellow River China's Ningxia Hui Autonomous Region (RUAN) was taken as an example present study. First, by establishing object-oriented remote sensing image classification system based Classification Regression Tree (CART), distribution years 2000, 2009 2018 were determined for a two-Stage (ST-I: 2000–2009, ST-II: 2009–2018) comparative research. Second, transition matrix landscape index used measure spatiotemporal dynamics two stages. Third, Pressure-State-Response (P-S-R) model, system, constructed comprehensively assess WEH there. Results revealed that: (1) Wetlands RUAN are dominated artificial ones, presenting overall increase area during statistical period, varying different trends Conversion between wetlands non-wetlands found frequent urbanization, leading remarkable changes patterns space. (2) Rivers basic forming RUAN, natural increased period. In general, patches diversity increased, shapes that became homogenized. Accordingly, aggregation decreased fragmentation worsened. (3) most experienced external pressure deterioration state, showing degradation. Meanwhile, more fundamental state itself, disturbance seemed function less. Above findings confirmed vulnerability urbanization arid circumstance. It worthy strengthening protection existing minimizing or eliminating conversion, ensure serve

Language: Английский

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Evolution of Wetland Patterns and Key Driving Forces in China’s Drylands

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(4), P. 702 - 702

Published: Feb. 17, 2024

Wetlands within dryland regions are highly sensitive to climate change and human activities. Based on three types of land use data sources from satellite images a spatial analysis, the spatiotemporal characteristics wetland evolution in China’s drylands their relationship with interference 1990 2020 were analyzed. The results as follows: (1) wetlands expanded, including rivers, lakes, artificial wetlands, apart marshes, which shrunk. Meanwhile, fragmentation increased, rivers being particularly severely fragmented. (2) Temperature precipitation showed an increasing trend drylands. Lakes expanded regional differences due uneven distribution rising temperature. (3) Human activities, more than change, became key driving factor for changes patterns increased areas farmland grassland along levels drainage irrigation activities led shrinkage marshes rivers. increase number reservoirs was main reason expansion wetlands. This study clarifies specific factors different drylands, is great better protecting gradual restoration degraded

Language: Английский

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Recognition of small water bodies under complex terrain based on SAR and optical image fusion algorithm

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 946, P. 174329 - 174329

Published: June 28, 2024

Language: Английский

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Synergistic mapping of urban tree canopy height using ICESat-2 data and GF-2 imagery

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2025, Volume and Issue: 136, P. 104348 - 104348

Published: Jan. 31, 2025

Language: Английский

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Tracking long-term wetland dynamics based on sample migration and two-stage hierarchical classification: A case study of Jiangsu Province

CATENA, Journal Year: 2025, Volume and Issue: 254, P. 108993 - 108993

Published: April 3, 2025

Language: Английский

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Quantitative Estimation of Organic Pollution in Inland Water Using Sentinel-2 Multispectral Imager

Sensors, Journal Year: 2025, Volume and Issue: 25(9), P. 2737 - 2737

Published: April 26, 2025

Organic pollution poses a significant threat to water security, making the monitoring of organic pollutants in environments essential for protection resources. Remote sensing technology, with its wide coverage, continuous capability, and cost-efficiency, overcomes limitations traditional methods, which are often time-consuming, labor-intensive, spatially restricted. As result, it has become an effective tool environments. In this study, we propose physically constrained remote algorithm quantitative estimation inland waters based on radiative transfer theory. The was applied Feilaixia Basin using Sentinel-2 data. Accuracy assessment results demonstrate good performance pollution, coefficient determination (R2) 0.79, mean absolute percentage error (MAPE) 13.03%, root square (RMSE) 0.39 mg/L. Additionally, seasonal variation map pollutant concentrations generated, providing valuable scientific support regional quality management.

Language: Английский

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Wetlands Mapping and Monitoring with Long-Term Time Series Satellite Data Based on Google Earth Engine, Random Forest, and Feature Optimization: A Case Study in Gansu Province, China

Land, Journal Year: 2024, Volume and Issue: 13(9), P. 1527 - 1527

Published: Sept. 20, 2024

Given global climate change and rapid land cover changes due to human activities, accurately identifying, extracting, monitoring the long-term evolution of wetland resources is profoundly significant, particularly in areas with fragile ecological conditions. Gansu Province, located northwest China, contains all types except coastal wetlands. The complexity its has resulted a lack accurate comprehensive information on changes. Using Province as case study, we employed GEE platform Landsat time-series satellite data, combining high-quality sample datasets feature-optimized multi-source feature sets. random forest algorithm was utilized create classification maps for across eight periods from 1987 2020 at 30 m resolution quantify area type. results showed that mapping method achieved robust results, an average overall accuracy (OA) 96.0% kappa coefficient 0.954 years. marsh type exhibited highest user (UA) producer (PA), 96.4% 95.2%, respectively. Multi-source aggregation optimization effectively improve accuracy. Topographic seasonal features were identified most important extraction, while textural least important. By 2020, total 10,575.49 km2, decrease 4536.86 km2 compared 1987. marshes decreased most, primarily converting into grasslands forests. River, lake, constructed generally increasing trend fluctuations. This study provides technical support protection offers reference mapping, monitoring, sustainable development arid semi-arid regions.

Language: Английский

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Dynamic Change Characteristics of Wetlands in Hefei and their Driving Factors Along the Urban–Rural Gradient

Wetlands, Journal Year: 2024, Volume and Issue: 44(7)

Published: Sept. 18, 2024

Language: Английский

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A blue–green ratio of urban wetlands as an ecosystem health indicator: the case of urban sprawl in Nagpur, India

Environmental Hazards, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 20

Published: Nov. 11, 2024

Rampant urban sprawl has affected the structure and function of existing green blue spaces, exposing developing cities to unexpected disaster events. Drawing on a mixture secondary information supported by GIS field-based studies, we assessed impact growing impervious surfaces dynamic zones wetlands in Nagpur, India. We compared decadal data (2000-2020) understand pattern wetland loss its drivers region. Our findings reveal significant area over past two decades, raising alarming concerns regarding ecological economic repercussions. To address these issues, propose blue–green buffer-based assessment approach that incorporates local knowledge observations along with proactive monitoring ecosystem health. study highlights urgency reducing spatial complexity landscape patches, restoring buffers, declaring buffers as no-go zones, promoting corridor connectivity improve infrastructure Multi-sectoral stakeholder cooperation, involvement, strict enforcement Wetland Rules (2017) governing bodies can help build resilience protecting infrastructure.

Language: Английский

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