Wetland Protection Research Articles

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

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

SMALL WETLANDS IN THE BRAZILIAN SAVANNA(CERRADO): AN UNDERESTIMATED FRESHWATER RESOURCE

In Brazil, in scientific research and public policy have largely ignored small wetlands, they are not specifically covered by current environmental laws and reference standards. Furthermore, the lack of information about, small wetlands has made their protection and management difficult. Large-scale land use changes that modify the hydrology of low-order streams often lead to the accelerated degradation and loss of small wetlands. The aim of this study conducted in Brazilian Cerrado Biome area, was to map the type, size, and distribution of small wetlands in ancatchment area). Areas represented in 12 high-resolution multispectral images were individually classified in a geographic object-based image analysis (GEOBIA), resulting in a sensitivity or recall 0.872 (~87%). The 7,132 mapped wetlands had a total area of 163km2, corresponding to a density of 4.27wetlands km−2, with smallest wetlands smaller than 4.0 hectares (90.5%). The following descriptors were applied to map small wetlands: feature: asymmetry, rectangular fit, mean nir band, compactness, density, and length. Seven types of natural wetlands and four types of man-made wetlands were accordingly identified in the study area. Their classification within a system that follows the hierarchy of the Brazilian wetland classification system is proposed. Recommendations for the future study and protection of wetlands was are also provided.

Comprehensive Landsat-Based Analysis of Long-Term Surface Water Dynamics over Wetlands and Waterbodies in North America

Wetlands are considered one of the most valuable ecosystems around the world and provide numerous environmental services, including water purification, flood protection, and habitat for a variety of species. Wetlands loss is an increasing trend due to anthropogenic activities and natural processes. As such, spatial knowledge regarding the extent and dynamics of surface water is demanding for wetland conservation and protection. The Landsat program, with five decades of historical Earth observation data, has a unique advantage for monitoring wetland surface water changes and dynamics with 30 m spatial resolution. We monitored 266 Ramsar wetland sites in North America for the past 40 years using the open-access Landsat data within the Google Earth Engine cloud computing platform. Landsat Collection 2 Level-2 surface reflectance products were preprocessed and cloud-screened, and a time series of spectral bands and indices were created. The unsupervised Dynamic Surface Water Extent method classified each image into water classes with different confidence levels. An average overall agreement of 92,97% and an average F-score of 96.31% were achieved in this study. Water occurrence maps, in addition to inundation class and change maps, were created for the entire North America, and quantified spatial information was calculated for Ramsar wetland sites.

Increasing marsh bird abundance in coastal wetlands of the Great Lakes, 2011–2021, likely caused by increasing water levels

Abstract Wetlands of the Laurentian Great Lakes of North America (i.e., lakes Superior, Michigan, Huron, Erie, and Ontario) provide critical habitat for marsh birds. We used 11 years (2011–2021) of data collected by the Great Lakes Coastal Wetland Monitoring Program at 1,962 point-count locations in 792 wetlands to quantify the first-ever annual abundance indices and trends of 18 marsh-breeding bird species in coastal wetlands throughout the entire Great Lakes. Nine species (50%) increased by 8–37% per year across all of the Great Lakes combined, whereas none decreased. Twelve species (67%) increased by 5–50% per year in at least 1 of the 5 Great Lakes, whereas only 3 species (17%) decreased by 2–10% per year in at least 1 of the lakes. There were more positive trends among lakes and species (n = 34, 48%) than negative trends (n = 5, 7%). These large increases are welcomed because most of the species are of conservation concern in the Great Lakes. Trends were likely caused by long-term, cyclical fluctuations in Great Lakes water levels. Lake levels increased over most of the study, which inundated vegetation and increased open water-vegetation interspersion and open water extent, all of which are known to positively influence abundance of most of the increasing species and negatively influence abundance of all of the decreasing species. Coastal wetlands may be more important for marsh birds than once thought if they provide high-lake-level-induced population pulses for species of conservation concern. Coastal wetland protection and restoration are of utmost importance to safeguard this process. Future climate projections show increases in lake levels over the coming decades, which will cause “coastal squeeze” of many wetlands if they are unable to migrate landward fast enough to keep pace. If this happens, less habitat will be available to support periodic pulses in marsh bird abundance, which appear to be important for regional population dynamics. Actions that allow landward migration of coastal wetlands during increasing lake levels by removing or preventing barriers to movement, such as shoreline hardening, will be useful for maintaining marsh bird breeding habitat in the Great Lakes.

Spatiotemporal disturbances and attribution analysis of mangrove in southern China from 1986 to 2020 based on time-series Landsat imagery

As one of the most productive ecosystems in the world, mangrove has a critical role to play in both the natural ecosystem and the human economic and social society. However, two thirds of the world's mangrove have been irreversibly damaged over the past 100 years, as a result of ongoing human activities and climate change. In this paper, adopting Landsat for the past 36 years as the data source, the detection of spatiotemporal changes of mangrove in southern China was carried out based on the Google Earth Engine (GEE) cloud platform using the LandTrendr algorithm. In addition, the attribution of mangrove disturbances was analyzed by a random forest algorithm. The results indicated the area of mangrove recovery (5174.64 hm2) was much larger than the area of mangrove disturbances (1625.40 hm2) over the 35-year period in the study area. The disturbances of mangrove in southern China were dominated by low and low-to-medium-level disturbances, with an area of 1009.89 hm2, accounting for 57.50 % of the total disturbances. The mangrove recovery was also dominated by low and low-to-medium-level recovery, with an area of 3239.19 hm2, accounting for 62.61 % of the total recovery area. Both human and natural factors interacted and influenced each other, together causing spatiotemporal disturbances of mangrove in southern China during 1986–2020. The mangrove disturbances in the Phase I (1986–2000) and Phase III (2011–2020) were characterized by human-induced (50.74 % and 58.86 %), such as construction of roads and aquaculture ponds. The mangrove disturbances in the Phase II (2001–2010) were dominated by natural factors (55.73 %), such as tides, flooding, and species invasions. It was also observed that the area of mangrove recovery in southern China increased dramatically from 1986 to 2020 due to the promulgation and implementation of the Chinese government's policy on mangrove protection, as well as increased human awareness of mangrove wetland protection.

Diatom and macroinvertebrate communities dynamic: A co-occurrence pattern analysis on plastic substrates

Wetlands are habitats that provide numerous ecosystem services, but are often understudied and threatened by anthropogenic pollution, particularly plastic pollution. Macroplastics are a significant component of plastic litter that have high biological impacts but are often understudied. Previous studies have highlighted negative impacts on biota, but there is a lack of information about the communities of micro and macro organisms that settle on macroplastic litter. In this context, we investigated the colonization patterns and community structures of diatoms and macroinvertebrates on virgin substrates composed of two different plastic polymers, polystyrene and polyethylene terephthalate, located at two different depths in a protected wetland in Central Italy over a period of 10 months. The results show that diatom community is not highly structured by competitive forces and aggregation patterns emerges. In contrast, macroinvertebrate community appears to be randomly structured, without the presence of patterns following specific assembly rules. Randomness in macroinvertebrates assemblages could highlight the presence of different niches available for settlement of different taxa. Combined matrix analyses show that diatoms and macroinvertebrates co-occur, and their community assemblages are sometimes structured, while they appeared to be randomly assembled at other times. Whenever non-randomness of diatoms and macroinvertebrates co-occurrences was detected, it suggested aggregation. Moreover, the possible predatory relationship between different macroinvertebrates taxa should be investigated, as it could reveal important scenarios in the establishment of macroinvertebrate structured communities on plastic litter, including taxa that exploit different ecological niches. This could lead to an enrichment of the biological community within areas impacted by plastics.

Comparison of avian diversity between managed and unmanaged wetlands in Patna, Bihar, India

Abstract We compared the bird diversity of a managed (Rajdhani Jalashay) and an unmanaged wetland (Mustafapur) in Patna, Bihar, India. We recorded bird species by using point counts and fixed-route monitoring. At Rajdhani Jalashay, a total of 73 species were recorded, of which 15 species were winter visitors. Two species were in the Near-threatened category: Ferruginous Duck (Aythya nyroca) and Alexandrine Parakeet (Psittacula eupatria), while the others were of least concern. At Mustafapur wetland, 67 species were recorded with 11 species as winter visitors. Simpson’s species diversity index was 0.78 at Rajdhani Jalashay, and 0.81 at Mustafapur wetland. The number of species of waders was 17 at Mustafapur wetland and 11 at Rajdhani Jalashay. The total number of Lesser Whistling-duck (Dendrocygna javanica), a resident bird was almost double (526) at Mustafapur wetland than that at Rajdhani Jalashay (234). The nitrate level was twice higher and the phosphate level was four times higher at Mustafapur wetland than those at Rajdhani Jalashay. The difference in species number and composition between the two wetlands may be attributed to the eutrophication resulting from high nitrate and phosphate levels at Mustafapur wetland. Unfortunately, the Mustafapur wetland is under threat due to human influences. The protection and sustainable management of natural wetlands is required for saving the biodiversity of the area.

The Unprecedented Ramsar Resolution: Ukrainian Wetlands Protection in Armed Conflict

Armed conflict has devastating environmental consequences, adversely impacting critical ecosystems and natural resources. The conflict between Russia and Ukraine, which has been ongoing since February 2022, has significantly affected Ukrainian wetlands, jeopardising their vital ecosystem services. The Convention on Wetlands of International Importance Especially as Waterfowl Habitat (‘Ramsar Convention’), which focuses on conserving and sustainably using wetlands, thus stands as a valuable tool for addressing environmental emergencies during armed conflict. With both Russia and Ukraine as Contracting Parties to the Ramsar Convention and their armed conflict causing a negative environmental impact, the effectiveness of the Ramsar Convention during such a conflict is being tested. The centrepiece of this article is a Resolution entitled ‘Environmental emergency in Ukraine relating to the damage of its wetlands of international importance (Ramsar Sites) stemming from the Russian Federation’s aggression’ recently adopted by the Conference of the Contracting Parties to the Ramsar Convention. This article assesses the effectiveness of the mechanisms within the Ramsar Convention and this Resolution in addressing the environmental challenges faced by Ukrainian Ramsar Sites during armed conflict. This case study provides broad insights into the overall challenges to implementing international environmental law treaties in times of armed conflict. Furthermore, it highlights the potential of leveraging the Ramsar Convention and similar environmental agreements to effectively safeguard the natural environment and ecosystems in times of armed conflict.

Habitat suitability assessment for Saunders's Gull (Saundersilarus saundersi) in the Yellow River Delta, China

The Yellow River Delta (YRD) is a key breeding place for Saunders's Gull (Saundersilarus saundersi), one of the vulnerable birds in the world. Thus, a thorough understanding of the key environmental factors influencing its suitable habitat holds great value for its conservation. Previous researches focused on Saunders's Gull's population changes and habitat features of breeding places in the nature reserve. However, its habitat suitability in the whole YRD has not been studied systematically, hindering the formulation of macro-protection policies to a certain extent. On the basis of occurrence records and environmental variables, we constructed an optimized MaxEnt model using the ‘kuenm’ R package to investigate the potential distribution of suitable habitat for the Saunders's Gull in the YRD. Results showed that the ideal hyperparameters for the MaxEnt model were a feature combination of linear and quadratic terms, and the regularization multiplier of 0.6 after optimization, indicated a high level of prediction accuracy. The environmental factors that had a significant effect on the Saunders's Gull's distribution were land use and land cover, percentage of beach saline–alkali land (PLAND_55) and distance to coastline (D_coastline). The highly suitable habitat had an area of 258.56 km2, of which 66.63% was located within the YRD National Nature Reserve. The management of constructed wetlands should be combined with the protection of natural wetlands to avoid the disadvantage of ‘isolated island-type’ protection. The study provides insights into the quantitative relationship between waterfowl and their habitat, providing support for the sustainable development of the YRD, with certain practical significance.

Fine-grained wetland classification for national wetland reserves using multi-source remote sensing data and Pixel Information Expert Engine (PIE-Engine)

ABSTRACT Timely and accurate wetland information is necessary for wetland resource management. Recent advances in machine learning and remote sensing have facilitated cost-effective monitoring of wetlands. However, reliable methods for fine-grained and rapid wetland mapping are still lacking. To address the issue, a wetland sample set with 20 categories for China was collected based on a sampling strategy that combines automatic sample generation and visual interpretation. Simultaneously, a novel multi-stage method for fine-grained wetland classification was proposed, which integrates pixel-based and object-based strategies using ensemble learning algorithms and multi-source remote sensing data. First, a pixel-based ensemble learning algorithm was implemented to classify five rough wetland categories and six non-wetland categories. Second, an object-based ensemble learning approach was designed to separate the water cover in the pixel-based classification results into eight detailed categories. Third, the merged pixel-based and object-based classification results were refined with knowledge-based post-processing procedures to identify 14 fine-grained wetland categories. Results using the Pixel Information Expert Engine (PIE-Engine) cloud platform proved the effectiveness of the proposed wetland classification method. The overall accuracy, kappa, and weighted F1 reached 87.39%, 82.80%, and 86.02%, respectively. The adopted ensemble learning algorithm yielded better performance than classifiers such as CatBoost, random forest, and XGBoost. The incorporation of spectral, texture, shape, topographic, and geographic features from multi-source data contributed to differentiating wetland categories. According to the relative contribution, spectral indexes (NDVI and NDWI), texture features (sum average and contrast), and topographic features (slope and elevation) were identified as important leading predictors for the first-stage pixel-based classification. Shape features (shape index and compactness) and auxiliary features (geographic location) were crucial predictors for the second-stage object-based classification. Compared with other products, our 10-m wetland mapping results for national wetland reserves were rich in detail and fine in categories. Overall, the constructed sample set and developed classification method show promise in laying a foundation for large-scale wetland mapping. The derived wetland maps can provide support for wetland protection and restoration.

Assessment of seasonal water quality and land use land cover change in Subarnarekha watershed of Ranchi stretch in Jharkhand.

In this paper, the assessment of seasonal water quality and land use land cover change in the Subarnarekha watershed in Ranchi stretch was analysed. Agricultural runoff along with climate change adds to the pollution risk to the Subarnarekha River of Ranchi stretch in Jharkhand. Water quality indicators, like acidity alkalinity (ALK), total dissolved solids (TDS), hardness (H), dissolved oxygen (DO), biochemical oxygen demand (BOD), chlorides (CL-), electrical conductivity (EC), salinity (SAL), resistivity (RES) and pH, were assessed as per the standard method. During monsoon season, acidity, alkalinity, hardness, chlorides, salinity, pH and DO decreased, whereas EC, TDS, BOD and resistivity increased in comparison to pre-monsoon season. In post-monsoon, chloride problem was observed very high. Hardness was least in monsoon and maximum in post-monsoon season. EC and BOD increased in monsoon season in comparison to other seasons. Statistical analysis like HCA (hierarchical cluster analysis) and PCA (principal component analysis) also confirmed the problem of TDS, EC, chloride and hardness in the area. WQI (water quality index) analysis showed that the water quality was poor to unsuitable on all the sampling points throughout the study area in all seasons. LULC (land use land cover) and NDWI (normalized difference water index) analysis had also concluded that due to high rate of urbanization, the area has undergone a massive change in terms of forest cover and water bodies. The need for afforestation, forest protection and wetland protection can be clearly seen from the result of this study.

Effects of urban land change on ecosystem service values in the Bolgoda Wetland, Sri Lanka

Understanding the effect of urbanization on urban wetland ecosystem service value (ESV) can provide scientifically sound information for urban planning and the protection of urban wetlands. This study aimed to discuss the effect of urbanization on the Bolgoda wetland, located in the Colombo Metropolitan Region (CMR), Sri Lanka. We developed a framework to evaluate the ESV changes based on land use/cover (LUC) changes between 1989 and 2021. Considering Natural Growth (NG) and Wetland Protection (WP) scenarios, we projected the future LUC changes (2030 and 2050) and evaluated the future ESV changes. The results revealed that the ESV has declined by USD 116 million/year from 1989 to 2021. The scenario analysis indicated that the ESV will continue to decrease by USD 17 million/year in 2030 and USD 35 million/year in 2050 under the NG scenario. However, under the WP scenario, the decrease would only be about USD 0.96 million/year in 2030 and USD 11 million/year in 2050, respectively. The most important ecosystem service functions are water regulation, genetic resources, food production, and climate regulation. Therefore, the local government should practice wetland management strategies to enhance the ESV of the Bolgoda wetland and other urban wetland ecosystems (UWEs) in the country.

HLEL: A wetland classification algorithm with self-learning capability, taking the Sanjiang Nature Reserve I as an example

Wetland ecosystems have been severely damaged by atmospheric pollution and other environmental problems for decades. Reasonable protection, restoration, and utilization of wetlands have become priorities for environmental protection. Obtaining high-precision wetland map products is essential for ecological research as well as formulation and implementation of conservation policies. This study proposes a hierarchical labeling ensemble learning (HLEL) algorithm with self-learning capabilities to achieve high-precision wetland land cover and land use (LULC) classification by adapting self-learning hierarchical results. This study evaluated the classification performance of HLEL, random forest (RF), support vector machine (SVM), artificial neural network (ANN), and Gaussian Naive Bayes' (GNB) with GF-6 WFV multispectral images as the database and Sanjiang National Nature Reserve I in China as the study area. The results showed that the HLEL algorithm has an advantage over a single algorithm when using the feature set filtered by ReliefF, even if the complete feature set is used without feature selection. The overall accuracy of the classification results is improved by 0.4%, 5.8%, 1.3%, and 9.0% when compared to the four single algorithms RF, SVM, ANN, and GNB, respectively. In robustness tests, HLEL consistently outperformed the other algorithms for different training sample set sizes, with overall accuracy improvements of 0.4–6.9%, 5.8–11.5%, 1.3–4.4%, and 9.0–14.0% compared with RF, SVM, ANN, and GNB, respectively. The overall accuracy standard deviation of HLEL is 1.22%, proving that HLEL has low sensitivity to the size of the training data. The HLEL algorithm demonstrates exceptional precision when applied to diverse datasets. The overall accuracy of HLEL in Sentinel 2, Landsat 8, and GF-6 WFV increased by 3.1% to 22.7%, 3.1% to 39.0%, and 0.4% to 9.0%, respectively, when compared to the overallaccuracy of the basicclassifiers. The results demonstrate the feasibility of HLEL, an algorithm with high accuracy and data robustness, in applying wetland LULC classification and providing a new solution for wetland cover mapping.

From separation to incorporation: Development of a unifying framework that integrated bird habitats with public recreation spaces within the wetland park system

The Ramsar Convention places central emphasis on the protection, restoration, and utilization of wetlands. Wetland species and their habitat protection is an important embodiment of wetland system protection. Simultaneously, the importance of recreation as a form of human activity within wetlands should not be underestimated. Wetland parks, as a mode of rational wetland use, provide the public opportunities for leisure and entertainment, exemplifying China's commitment to the Ramsar Convention on Wetlands. However, With the acceleration of urbanization, the degree of fragmentation of the wetland system is increasing. The wetland park and its surrounding landscape elements are separated from each other, resulting in the phenomenon of islanding, which is not conducive to the protection and utilization of wetland biodiversity. This study focuses on Yancheng coastal wetland, a UNESCO World Heritage site in Jiangsu, China, as its research area. It integrates habitat birds, a core component of wetland biodiversity, into the development framework of wetland parks. The study proposes the use of composite habitat corridors to connect fragmented bird habitats with public recreational areas, establishing a collaborative wetland park system. The methodology involved three key steps: (1)Spatial Modeling. Utilizing Maxent, the spatial distribution of birds and public recreation areas was modeled, and suitable patches for both were extracted. (2) Corridor Identification. Linkage Mapper was employed to identify bird and recreational corridors, while the MCR model was used to pinpoint composite habitat corridors. (3) Network Development. Corridors generated in the previous step were superimposed on the ArcGIS platform to create a network of interconnected bird habitats and public recreation areas within the wetland park system. The study's results demonstrate: (1) There are obvious spatial distribution differences between the current core bird habitat and public recreation areas in Yancheng coastal wetland. (2) The establishment of a composite corridor network realizes the interconnection between bird habitats and public recreation areas，among them, the corridor network in the southern region is short and dense, with higher stability. (3) The areas passed by the composite corridor network are mainly productive landscapes such as cultivated land and aquaculture ponds, and therefore, certain protection and restoration measures should be taken to create suitable habitat conditions for birds and humans. This study provides a novel model for wetland protection and sustainable utilization, particularly relevant to many developing countries facing similar challenges.

Optimization of wetland water replenishment process based on the response of waterbirds in a semi-arid and cold region

Emergency ecological water replenishment(EEWR) has become a major strategy for recovering degraded wetland ecosystems worldwide. However, the actual replenishment process mainly depended on the tradeoff and experience between the managers of Taoer River and Xianghai Wetland, which is very random and lacks theoretical guidance. Thus, there is urge to assessing water replenishment effect on wetland and help to optimize the process. With contrasting results as different ecosystem elements respond differently, the optimization of water replenishment process should be based on the improvement of the ecosystem as whole rather than its separate elements. However, the dynamic monitoring of biotic and abiotic factors to reveal the complex relationships underlying their response can be challenging. Based on 6 years’ series data of migratory birds and environmental factors of Xianghai Wetland, which started emergency ecological water replenishment since 2004 and occurred frequently since 2011, the broader ecosystem response to water replenishment was analyzed using a multiple paths regression model and proposed an optimized scheme. The results showed that bird diversity was positively influenced by the increase in water area and vegetation was induced by ecological water replenishment. While the response of bird abundance to water replenishment varied with time, adequate open water in March was found to have a positive relationship with abundance by promoting vegetation germination and the reproduction of benthic organisms. High flow levels in the wet season (June–August) can negatively affect waterbird abundance by rapidly increasing water levels and inhibiting plant respiration, which leads to the reduction in feeding efficiency of waterbirds and biomass accumulation. Therefore, the existing ecological water replenishment time (May–September) is not suitable for bird abundance and should be advanced to spring (March–April). Given the antagonistic effect of flow on diversity and abundance, the total replenished water should be approximately 100 million m3. To avoid the negative influence of high water in the wet season, the allocation of water could be 0.3, 0.3, 0.2, and 0.2 million m3 in April, May, September, and October, respectively. These results scientifically support wetland protection and management.

Mangrove forest mapping from object-oriented multi-feature ensemble classification using Sentinel-2 images

Accurate mapping of mangrove forests is crucial for understanding their ecosystem function and developing effective management policies. However, the absence of an operational multi-feature fusion approach and an ensemble classification system restricts the achievement of this goal. This study aims to develop an object-oriented multi-feature ensemble classification scheme (OMEC). First, an enhanced mangrove spectral index (EMSI) is established by analyzing the spectral reflectance differences between mangrove forests and other land cover types. Sentinel-2 images are segmented into objects using the multi-resolution segmentation method. Then, spectral, textural, and geometric features are extracted, and these features (including EMSI) are inputted into the nearest neighbor classifier to implement mangrove classification. The experiment was conducted in three typical mangrove areas in China using Sentinle-2 images. The results demonstrate that EMSI exhibits good spectral separability for mangroves and performs well in the ensemble classification scheme. The overall accuracy of mangrove classification exceeds 90%, with a Kappa coefficient greater than 0.88. The object-oriented multi-feature ensemble classification scheme significantly improves accuracy and exhibits excellent performance. The method enhances the accuracy of mangrove classification, enriches the approach to mangrove remote sensing interpretation, and offers data support and scientific references for the restoration, management, and protection of coastal wetlands.

Mapping Coastal Wetlands and Their Dynamics in the Yellow River Delta over Last Three Decades: Based on a Spectral Endmember Space

The accurate mapping and analysis of coastal wetlands and their dynamics are crucial for local coastal wetland protection, sustainable social development, and biodiversity preservation. However, detailed mapping and comprehensive analysis of coastal wetlands remain scarce. In this study, we utilized Landsat-TM/OLI remote sensing data and employed the linear spectral mixture analysis (LSMA) method to map changes in coastal wetlands and analyze their dynamics in the Yellow River Delta (YRD) from 1991 to 2020. Our mapping results demonstrate high accuracy and are consistent with previous studies, boasting an overall accuracy exceeding 96%. During the period of 1991–2020, the YRD estuary expanded by approximately 8744.58 ha towards the east and north. The vegetation of P. australis and S. salsa underwent transformation due to agricultural practices or degradation to bare flats. Moreover, these areas saw extensive colonization by the invasive species S. alterniflora. Over the three decades, S. alterniflora expanded approximately 5 km along the coast, significantly impacting the local coastal wetland biodiversity. Furthermore, a considerable number of natural wetlands transitioned into human-made wetlands from 1991 to 2014. In particular, bare flats underwent substantial changes, transforming into aquaculture sites and salt exploitation areas. These dynamics in coastal wetlands had significant repercussions on local ecosystems, including wetland fragmentation, biodiversity depletion, and water pollution. However, post-2014, numerous wetland protection strategies were implemented, resulting in the restoration of natural wetlands. Detailed wetland mapping and dynamic analysis furnish valuable insights for the management, protection, and sustainable utilization of diverse coastal wetlands.

Simulation and analysis of red-crowned crane habitat suitability using maximum entropy and information entropy models

The red-crowned crane (Grus japonensis) is a rare waterfowl species that is sensitive to environmental changes in its habitat selection; as such it effectively reflects the variation in wetland landscapes. Therefore, analysis of the habitat suitability for the red-crowned crane can be used to determine the species requirements and to predict its potential habitat distribution, thereby providing a basis for the protection of wetlands and endangered species. In this study, the Landsat satellite remote sensing data of Zhalong Wetland from 1996 to 2019 were used to simulate the nest coordinates of red-crowned cranes using a binary logistic model and to simulate the distribution of suitable habitat via a maximum entropy model. Moreover, an information entropy model was used to examine the yearly changes in habitat suitability and the underlying mechanisms and influencing factors. These two entropy models were combined to simulate the habitat suitability distribution and variation with high accuracy, determine the contribution rates of influencing factors, and provide data for analyzing interannual changes. The following results were obtained. First, the habitat suitability was highest in the center, core area and decreased towards the periphery of Zhalong Wetland. Second, the habitat suitability increased in some regions in the south, decreased in some areas in the north, and remained unchanged in the majority of the peripheral regions. Third, habitat suitability was primarily impacted by landscape patterns, distances to rivers and ditches, and vegetation. Red-crowned cranes preferred to reside far from human disturbance in wetlands near rivers with reeds (Phragmites australis) as the dominant species.

Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data

Accurate information on lake bathymetry and water dynamics is crucial for comprehending the intricate ecological processes in wetland ecosystems, which in turn can inform effective conservation and management strategies. However, obtaining such information can be challenging, particularly in remote areas with limited data. This study presents a way to leverage inundation frequency and ICESat-2 photon-counting LiDAR data to develop bathymetric models for Ramsar-listed lakes in a semi-arid region of Australia. Based on developed bathymetric models, monthly time series of water areas, levels and volumes were derived, providing a long-term view of the water dynamics of the two lakes from1987-2021. This is the first time that such detailed bathymetry and long-term water dynamics have been established for Ramsar-listed lakes in Australia's Outback. The findings of this study provide the most up-to-date information on the long-term trends of the Ramsar-listed lakes in the region and highlight the lakes’ prolonged dry spells when drought conditions prevailed through much of the 2000s and the 2010s as denoted by rainfall deficiencies and high evaporation. The outcome of this study serves as a valuable baseline for understanding the historical and ongoing status of these Ramsar-listed lakes in a warming and drying climate and contributes to the development of strategic plans to fulfill international obligations for wetland protection under the Ramsar Convention.

Dynamic changes in net primary productivity of marsh wetland vegetation in China from 2005 to 2015

Wetlands are one of the world's three major ecosystems. Marsh wetland vegetation, with its unique characteristics, is playing an increasingly prominent role in absorbing atmospheric carbon dioxide and mitigating climate warming. This study estimated the annual, seasonal, and monthly trends of marsh wetland vegetation net primary productivity (NPP) in China from 2005 to 2015 based on the Carnegie–Ames–Stanford approach (CASA) model. The temporal and spatial characteristics of NPP were analyzed and the driving factors were discussed. The results showed that the annual marsh wetland vegetation NPP had an increasing trend from 2005 to 2015 on national scale in China, with the lowest and highest values in 2005 (202.03 gCm−2a−1) and 2015 (222.58 gCm−2a−1), respectively. The monthly seasonal variations in marsh wetland vegetation NPP consistent with the typical growth pattern of vegetation observed in China. Monthly marsh wetland vegetation NPP showed a unimodal distribution, and May to September were the main months for NPP accumulation. The highest vegetation NPP values occurred during the summer season. Marsh wetland vegetation types did impact the NPP distribution, Gramineous marsh vegetation contributed most to the total NPP (29%). Spatially, the NPP was higher in east than in the west, and higher in the center than in the south and north. An overall positive impact of precipitation and temperature on the Chinese marsh wetland vegetation NPP was revealed. The study recommended to give greater attention the conservation of Gramineous vegetation alongside the overall protection of Chinese marsh wetlands. Our findings can offer important evaluation results and guidance for the future addressing climate change and conservation and maintenance of the carbon sink capacity of marsh wetland vegetation in China.