Dongting Lake Area Research Articles

Effect of Harvesting Time on Biomass and Combustion Quality of Miscanthus lutarioriparius in Dongting Lake Area

Effect of Harvesting Time on Biomass and Combustion Quality of Miscanthus lutarioriparius in Dongting Lake Area

Landscape Character and Management Zones in Polder Landscapes: A Case Study of the Dongting Lake Area

Polder landscapes, as a representative of lowland agriculture landscapes, possess diverse natural and cultural values. However, polder landscapes are facing multiple challenges arising from economic and climate changes, including increasing flood threats and the fragmentation of landscape patterns. These issues have severely threatened the safety and regional characteristics of the polder landscape. Therefore, this study aims to preserve the regional characteristics of polder landscapes while promoting the sustainable development of lowland environments, and the objective is to provide a foundation and baseline for the management and planning of polder landscapes. In this study, the Dongting Lake Area (DLA) was selected as a representative case of polder landscapes. To identify the landscape character and delineate the landscape management zones, this study employed the Landscape Character Assessment (LCA) method in conjunction with a polder typology method at two scales. As a result, the polder landscape types were identified and visualized at two different scales. At the Lake Scale, a comprehensive identification method for polder unit types and polder landscape regions was established, achieving a stepwise transition from polder areas to polder clusters and ultimately to individual polder units. At the Local Scale, an integrative analysis of landscape character diversity (LCD) and land construction suitability (LCS) was employed to establish five landscape management zones for polder landscapes, thereby realizing a balance between the conservation of polder landscape diversity with the sustainable development of wetland environments. This study contributes a set of cross-scale ideas and methods for identifying landscape characters and delineating management zones in polder landscapes, which could be expanded to other lowland agricultural landscapes.

Current state, sources, and potential risk of heavy metals in sediments of typical inner lakes in the Dongting Lake Area

The region has been increasingly experiencing environmental issues related to heavy metals (HMs) due to human activities. However, the contamination levels of HMs (Cr, Ni, Cu, Zn, As, Cd, and Pb) in various inner lakes in the Dongting Lake area remain unclear. In this study, surface sediment samples from 9 inner lakes and sediment core samples from 3 typical inner lakes were collected to evaluate the spatial distribution, contamination status, environmental and ecological risks, and possible sources of these HMs. The results showed that all HMs, except Zn, exceeded background values, with particularly high levels observed in aquaculture lakes compared to other lakes. Vertical profiles of HMs from 3 lakes show that the various types of lakes in the study area have different pollution histories. Additionally, results from Sediment quality guidelines (SQGs), Contamination factor (CF), Geo-accumulation index method (Igeo), and Hakanson potential ecological risk index (PERI) indicated that As, Cd, and Pb are the primary pollutants. The multivariate analysis concluded that Ni, Cu, Zn, As, Cd, and Pb had anthropogenic sources, primarily from agricultural, fisheries, industrial, and transportation activities, while Cr was influenced by natural factors. The results of this study enhance our understanding of sedimentary metal content in inner lakes and emphasize the importance of controlling HMs content in these lakes. This information is crucial for developing effective lake management and pollution control strategies.

Impacts of the land use transition on ecosystem services in the Dongting Lake area

Urbanization-induced land use transitions (LUTs) result in a decline in ecosystem services, which has implications for regional ecological security. In order to explore the relationship between ecosystem services and land use transition, this paper utilizes the InVEST model, a geographically weighted regression (GWR) model, to examine the impact of land use transition on ecosystem services in the Dongting Lake area (DLA). The results showed that 1) with the change in urbanization development, the average values of land use transition intensity (LUI) in 2000, 2010, and 2020 are 237.99, 235.82, and 238.92, respectively. Land use dynamics (LUD) show a tendency to increase and then decrease, with average values of 5.58 and 5.62 for the periods 2000–2010 and 2010–2020, respectively, and the transformation of land use shows obvious spatio-temporal heterogeneity. 2) Habitat quality and carbon sequestration showed a downward trend. In contrast, food supply followed an upward trend; soil conservation (SC) and water yield (WY) services initially increased and decreased later. The overall spatial changes in habitat quality and carbon sequestration appear to be insignificant. Food supply shows significant differences in the plains compared to other areas, while soil conservation and water yield service show significant changes in places other than the DLA. 3) From 2000 to 2020, land use transition dynamics, population density, GDP density, night lighting, and transition intensity had mainly negative effects on ecosystem services. Only the Normalized Vegetation Index (NDVI) showed a positive effect on ecosystem services. The results of the research will provide valuable references for the development and implementation of spatial ecological restoration planning and land use policies in the national territory.

Refining Long-Time Series of Urban Built-Up-Area Extraction Based on Night-Time Light—A Case Study of the Dongting Lake Area in China

By studying the development law of urbanization, the problems of disorderly expansion and resource wastage in urban built-up areas can be effectively avoided, which is crucial for the long-term sustainable development of cities. This study proposes a high-precision urban built-up-area extraction method for county-level cities for small and medium-sized towns in county-level regions. Our process is based on the Defense Meteorological Satellite/Operational Linescan System (DMSP/OLS) and the NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS), which develops long-term series of coordinated night-time light (NTL) datasets. We then combined this with the Normalized Vegetation Index (NDVI) to calculate the Vegetation-Adjusted NTL Urban Index (VANUI). We combine land use data and a support vector machine (SVM) for semi-supervised classification learning to propose a high-precision urban built-up-area extraction method for county-level cities. We achieved the following results: (1) we fit binary polynomials to the DMSP/OLS and VIIRS NTL datasets based on the correspondence of the mean values to construct a consistent time series of NTL data. (2) Our method effectively improves the accuracy of urban built-up-area extraction, especially for county-level cities, with an overall accuracy of 91.84% and a Kappa coefficient of 0.83. (3) Our method can perform a long-time series of urban built-up-area extraction, and, by studying the spatial and temporal changes in urban built-up areas, it can provide valuable information for sustainable urban development and urban planning.

High-quality agricultural development in the central China: Empirical analysis based on the Dongting Lake area

High-quality agricultural development constitutes the primary point for forthcoming agricultural and rural endeavors. This study aimed to analyze the characteristics and obstacle factors of the high-quality agricultural development in central China, and the Dongting Lake area was taken as a case. Statistical data, land use data, and other data were adopted, and GIS spatial analysis and mapping technologies, obstacle model, and entropy weight method were used. The research results indicated that: 1) The comprehensive index has increased from 0.4290 in 2010 to 0.4717 in 2020. The change rates of the subsystem ranked from the highest to the lowest were as follows: cultural construction (36.25 %), ecological environment (15.18 %), social security (4.42 %), and material output (2.63 %). 2) The composite index has changed from higher in the west and lower in the east to a unconspicuous spatial difference. The material production index has shifted from higher in the north and lower in the south to a scattered distribution. The social security index has changed from higher in the west and lower in the east to higher in the northwest southeast and lower in the centre. The ecological environment index was higher in the west and lower in the east. The cultural construction index was higher in east and west and lower in the centre. 3) The top 4 obstacle factors were the high-quality development platforms, the agricultural driving force of per cultivated land, the number of agricultural geographical indication and the grain yield of per cultivated land. At the same time, the material output was the biggest obstacle. It is recommended to focus on the agricultural cultural resources in the eastern and western parts. This study can provide guidance and methodological references for similar studies, as well as scientific references for the sustainability of agriculture and optimization of related policies.

Exploring the impacts of land use and land cover change on ecosystem services in Dongting Lake, China: a spatial and temporal analysis

Background and objectives: Land use and land cover change (LULCC) directly affects the human living environment and economic society by influencing ecosystem services. This study explores the complex relationship between LULCC and ecosystem services in the Dongting Lake region of China.Methods: The analysis incorporates the transfer matrix analysis of LULCC, ecosystem service value (ESV) accounting, Mann–Kendall mutation test, gray correlation, and path analysis. This study explored the spatial and temporal characteristics of LULCC and ecosystem services and revealed the comprehensive impacts of LULCC on ecosystem services from the perspective of factor interactions.Findings: The findings reveal that open water (OW) area and farmable land are the dominant land use types transferring in and out of the study area, with significant interconversion observed among open water area, wetland (WL), arable land (AL), and forest land (FL). Water conservation, waste disposal, climate regulation, and biodiversity conservation emerge as the most crucial ecosystem services in the study area. The study identifies consistent patterns of abrupt changes in LULCC and ESV across six analyzed time periods. Forest land exhibits the most substantial direct influence on climate regulation, gas exchange, soil formation and protection, conservation of biodiversity, raw materials, and recreation and leisure. Additionally, forest land, wetland, arable land, and open water area contribute significantly to the total ESV, with forest land being the dominant factor influencing the spatial differentiation of ecosystem services in the Dongting Lake region.Conclusion: The research reveals the consistency of ecosystem services and LULCC trends in the Dongting Lake area. LULCC is a complex process influenced by multiple factors, in which the conversion between ecological and non-ecological land use has a significant impact, and the complex coupling and coordination among LULCC drivers together influence ecosystem services. Furthermore, LULCC alters the structure and scale of ecosystems, resulting in alterations in the ESV.

A Study on the Spatial Structures and Mechanisms of Intangible Cultural Heritage and Traditional Villages in the Dongting Lake Basin

This study focuses on 1209 national and provincial intangible cultural heritage items and 1234 traditional Chinese villages within the Dongting Lake Basin. Using kernel density analysis, centroid models, coupling models, and quantitative spatial–structural models, the present research analyzes the spatial–structural characteristics and formation mechanisms of intangible cultural heritage and traditional villages to provide scientific support for their preservation, inheritance, and effective utilization. The results revealed the following: (1) Intangible cultural heritage and traditional villages in the Dongting Lake Basin exhibit a very concentrated spatial distribution, with similar spatial–structural characteristics. (2) High spatial coupling of intangible cultural heritage and traditional villages is observable in the sub-basins of Dongting Lake, such as the Yuanjiang, Zishui, and Lishui basins, whereas the Xiangjiang Basin and Dongting Lake area present relatively lower levels of spatial coupling. In terms of the categories of intangible cultural heritage, four of them—cultural heritage, folk literature, traditional music, traditional dance, and traditional drama—have the smallest deviation distance and index values from traditional villages. The coupling degree was higher than 0.70, and there were some differences in the coupling degree between the other six categories of intangible cultural heritage and traditional villages. (3) The spatial–structural characteristics of intangible cultural heritage and traditional villages in the Dongting Lake Basin emerged from the combined effects of multiple factors, including internal connections between the two, as well as external factors such as the natural environment, socio-economic conditions, and cultural policies, all of which play crucial roles in the formation processes of these characteristics.

Rodent-Proof Wall: An Efficient Physical Method for Controlling Rodents and its Efficiency Statistics.

Rodent damage poses a significant threat to crops, human life, and health. Compared to chemical rodent control, such as placing poisonous baits, it is more economical and environmentally friendly to use physical methods, such as building a rodent-proof wall. This study introduces a method of physically controlling harmful rodents and four methods of calculating the effect of rodents control. To understand the controlling effect of the rodent-proof wall, an investigation was conducted on the Dongting Lake beach and corresponding farmland in the embankment in April and July 2012. Our findings illustrated that the density of the reed vole Microtus fortis in the farmland with rodent-proof walls was 0.52%, significantly lower than that in the farmland without rodent-proof walls (1.76%) after artificial trapping and drug extermination (χ2 = 3.900, P = 0.048). The density of M. fortis that had migrated into the farmland in dikes with a rodent-proof wall decreased by 98.53%, significantly higher than the decrease of density in dikes without a rodent-proof wall (86.61%) (χ2 = 11.060, P = 0.01). The results demonstrated the effectiveness of rodent-proof wall control. Therefore, building a rodent-proof wall should be advocated and vigorously promoted to prevent the migration of rodents into the Dongting Lake area and similar environments, as they cause harm.

Study on the factors influencing ecological environment and zoning control: a study case of the Dongting Lake area

IntroductionProtecting the ecosystem of the Dongting Lake area is of utmost importance for maintaining ecological balance and achieving human well-being.MethodsThis study identifies the key factors influencing the remote sensing based ecological index (RESI) in the Dongting Lake area based on the spatial and temporal evolution characteristics of the RESI and environmental changes and anthropogenic disturbance factors. The priority zoning for ecological restoration was delineated in combination with the anthropogenic composite index (ACI). By exploring the influence of anthropogenic disturbances on RESI, the zoning locations were determined using spatial statistics and linear regression methods.ResultsThe overall RESI of the Dongting Lake area showed a decline from 2001 to 2020, with the mean value decreasing from 0.52 to 0.48. High-quality zones were mainly located in mountainous and forested areas, while low-quality zones were mainly distributed in more developed cities in the east urban area. Anthropogenic factors were the main reasons for the decline in the ecological environment, while natural factors showed a positive correlation with RESI. Based on the RESI and ACI, four ecological control zones (H-H, H-L, L-H, and L-L) were delineated, which accounted for a total of 45.66% of the Dongting Lake area. Among them, 3.91% required immediate control and management, while 17.80% required artificial maintenance. This study explores the influencing factors and mechanisms of the ecological environment quality in the Dongting Lake area, and explores the effective spatial paths for the implementation of ecological restoration zoning control and differentiated restoration strategies in the Dongting Lake area.DiscussionThis study provides a scientific basis for mitigating ecological and environmental problems in the Dongting Lake area, and provides a reference for ecological restoration and regulation and the realization of sustainable development goals in China and global regions with complex environmental problems.

Spatiotemporal evolution and driving factors of tourism ecological adaptation in the Dongting Lake Area, China

Tourism ecological adaptation (TEA) offers a novel research framework and practical tool for analyzing sustainable regional development. This facilitates high-quality tourism development, safeguards the ecosystem, and enhances risk resilience. However, existing TEA research has shortcomings regarding methodology and research scales. This study constructed a TEA index system to address these deficiencies. The index system comprises two subsystems, tourism industry adaptation (TIA) and ecological environment adaptation (EEA), including three dimensions: sensitivity, stability, and response. The entropy-weighted TOPSIS method, adaptation assessment model, standard deviation ellipse, and geographic detector were used to analyze the spatiotemporal evolution and driving factors of TEA in the Dongting Lake area, China, from 2012 to 2021. The TIA index displays a rise-fall-rise pattern, whereas the EEA index demonstrates a fluctuating upward trend. Additionally, the TEA index exhibits a distinctive basin-type spatial distribution pattern, with lower values in the central region and higher values in the surrounding areas. Over the past decade, standard deviation ellipses of adaptability have shown minimal changes in shape, position, and center. Both the clustering and center positions reached a state of basic equilibrium. The predominant TEA type was characterized by low adaptation, including 41.18% of the counties. The spatiotemporal evolution of TEA is driven by tourism resource endowment, government regulatory efforts, level of economic development, and environmental governance capacity

Climatic Characteristics of Heavy Snowfall and the Water Vapor Transport Characteristics in Typical Snowfall Events in Hunan Province of China

Due to the unique topography and geographical location, severe snowfall is the main disastrous weather in winter in the Hunan Province of China. Based on the daily precipitation data in Hunan Province from 1961 to 2021, the regional heavy snowfall processes are classified by using the synoptic diagnostic method. In addition, the water vapor transport characteristics of typical heavy snowfall processes are analyzed by the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) air mass backward trajectory model. Then, the responses of the differences in water vapor transport to heavy snowfall under different weather situations are discussed. The results show that the spatial distribution of climatic mean heavy snowfall days in Hunan Province is extremely uneven, and the heavy snowfall days decrease from north to south, with the most in the Dongting Lake area and the least in the Nanling Mountains. In the past decades, snowstorms mainly occur in local areas, and there are fewer widespread snowstorms. The frequency of heavy snowfall days generally shows a decreasing trend, with three peaks all appearing before 1990. After the 2010s, the number of days and stations of heavy snowfall decreased noticeably, and so did the number of regional heavy snowfall processes. This result indicates that global warming has remarkable effects on the snowstorm events in Hunan Province. Heavy snowfall mainly occurs from December to February, and peaks from mid-January to early February. Over the past 61 years, more than 50% of heavy snowstorm events occurred after 2000. According to the main weather systems affecting regional heavy snowfall processes, these weather processes in Hunan Province can be classified into three categories: southern branch trough (SBT) type, blocking high collapse (BHC) type, and stepped trough type. Among them, the SBT type accounts for more than 60% of the heavy snowfall events in Hunan. In terms of the SBT type and the stepped trough type, the water vapor from the high-latitude inland and low-latitude sea surface accounts for a comparable proportion, each accounting for nearly 50%. For the SBT type, the proportion of the water vapor from warm-humid airflows is slightly higher than that from cold-humid airflows. However, in terms of the stepped trough type, the water vapor transported by cold-humid airflows from the north contributes more than that by warm-humid airflows. For the BHC type, the specific humidity and the water vapor from the high-latitude inland contribute 70% of heavy snowfall processes. In addition, the contribution of the two southwesterly water vapor channels to heavy snowfall processes is small. The water vapor sources differ remarkably for different heavy snowfall types, but all of them are dominated by the water vapor transport in the middle and lower troposphere, which is the main reason why the formation of snowfall areas under different weather types is obviously different.

Digital research on the resilience control of water ecological space under the concept of urban-water coupling

Introduction: The construction of digital governance of national land space depends greatly on the development of a digital model for robust control of water and ecological space. However, how changes to the urban-water coupling relationships affect the resilience control of water ecological space is rarely reported.Methods: The evolution characteristics of urban and water space in the study area from 2000 to 2020 and the correlation between them are analyzed based on the grid analysis using InVEST and Moran’I methods. Based on the theory of human-environment interaction territorial system to provide a theoretical framework to explain the urban and water space. We used digital to construct an resilience control framework in the Dongting Lake area based on the correlation between the urban and water space.Results: The results show that: 1) From 2000 to 2020, the geographical evolution of towns and cities in the research area displayed obvious spatial variation in intensity, indicating a process of expansion and change. The regional and temporal fluctuations of the water conservation function are significant. The mountainous areas in the east, south, and northwest are where the high values of the water conservation function are primarily found. These regions have more vegetation, which increases the water conservation function. 2) According to the results of local binary spatial autocorrelation analysis, it can be seen that from 2000 to 2020, the high-high agglomeration of town space and water-related is mainly distributed in Linxiang City, Yueyang County, Miluo City, Li County, and Yiyang City, and the low-low agglomeration is mainly distributed in Dongting Lake, Datong Lake, and along the Yangtze River. 3) Based on how urban spatial evolution affects water ecological space, we construct a theoretical framework of urban-water coupling and establish a digital model of water ecological space resilience control in the Dongting Lake area from four perspectives: threshold, visualization, dynamics, and intelligence.

Monitoring of wetland cover changes in protected areas to trade-offs between ecological conservation and food security: A case study from the Dongting Lake, China

The United Nations' Sustainable Development Goals (SDGs) for 2030 underscore the urgency of “eradicating hunger and ensuring food security” (SDG 2: Zero Hunger) and the critical need to “cease and reverse land degradation and biodiversity decline” (SDG 15: Life on Land). The Dongting Lake area in China, serving as a significant wetland nature reserve and grain production zone, is increasingly confronted with complex, interdependent trade-offs between agricultural cultivation and the ecological and environmental preservation of wetlands (SDG 2 and 15). To analyze the trade-off between conservation and food security, it is crucial to rely on long-term, continuous monitoring of land cover changes in the lake area. However, the absence of reliable optical remote sensing has posed a significant challenge due to the prevalence of cloudy and rainy conditions. Our study begins by integrating long-term Landsat and MODIS data using the GF-SG fusion algorithm to generate 8-day NDVI data with a spatial resolution of 30 m. This analysis focuses on the areas outside the embankment of Dongting Lake (referred to as O-DTL) from 2003 to 2020. We then employ a pixel-connected sample migration method to facilitate automated sampling of land cover types and a random forest classification algorithm to analyze long-term dynamic changes. Finally, by combining meteorological and social data, we examine the temporal patterns of land cover changes in the study area and identify the underlying factors influencing them. The results indicate a trade-off between the fluctuation of cropland and forest area from 2003 to 2020. Water body areas have exhibited a significant decrease, while impervious surface areas have consistently increased annually. Impervious surface areas have experienced a substantial increase of approximately 70%, with almost 90% of this expansion resulting from the conversion of cropland. Under the premise of maintaining a stable area for food cultivation, the land consumed by urban expansion eventually encroached on the wetland water bodies of the reserve. The reduction in wetland water area in the O-DTL can be primarily attributed to agricultural cultivation, while urban expansion and urbanization have indirectly contributed to the decrease. This study provides a case in which prioritizing food security (SDG 2) takes precedence over ecological conservation (SDG 15), highlighting its significant implications for guiding subsequent development in the Dongting Lake area. This finding is crucial for minimizing unintended consequences and maximizing co-benefits between sustainable development goals.

Driving Mechanisms of Spatiotemporal Heterogeneity of Land Use Conflicts and Simulation under Multiple Scenarios in Dongting Lake Area

As an important ecological hinterland in Hunan Province, the Dongting Lake area has an irreplaceable role in regional socioeconomic development. However, owing to rapid environmental changes and complex land use relationships, land use/land cover (LULC) changes are actively occurring in the region. Therefore, assessment of the current LULC status and the future development trend for sustainable economic development is of considerable importance. In this study, the driving mechanisms of spatiotemporal evolution for land use conflicts (LUCF) in Dongting Lake from 2000 to 2020 were analyzed by constructing a LUCF model. Additionally, a new model, EnKF-PLUS, which couples ensemble Kalman filtering (EnKF) with patch-generating land use simulation (PLUS), was developed to predict the LULC changes and LUCF in 2030 under different scenarios. The results provide three insights. First, during the period of 2000–2020, high LUCF values were concentrated in highly urbanized and densely populated areas, whereas low LUCF values were centered in hilly regions. Secondly, the impacts of static factors (topographical factors) and dynamic factors (population, GDP, and climate factors) on changes in LUCF were regionally differentiated. Thirdly, our results indicate that the implementation of land use strategies of cropland conservation and ecological conservation can effectively mitigate the degree of LUCF changes in the region and contribute to the promotion of the rational allocation of land resources.

The Coordinated Development of Ecosystem Services and Farming Household Livelihood Security: A Case Study of the Dongting Lake Area in China

Ecosystem services (ESs) are an important basis for maintaining farming household livelihood security and achieving the synergistic and efficient development of ecosystem services, and farming household livelihood security is important for maintaining sustainable development in the region. However, it is difficult to quantify the level of the coordinated development of ESs and farming household livelihood security in a region and their dynamic evolution. This study systematically analyzes the spatio-temporal evolution of the production-living-ecological space, ecosystem service values, and farming household livelihood security in the Dongting Lake from 2000 to 2020 based on land use data, as well as the level of coordinated development of ESs and livelihood security of farmers. The results indicate that more than 80% of the Dongting Lake area has a low level of coordinated development of ESs and farming household livelihood security at or below the level of imminent disorder, but it is on the rise, increasing by 6.32% in the past twenty years. This study can provide a reference for decision-making on the coordinated development of ecological environment and farmers’ livelihoods in the Dongting Lake area.

Unlocking the potential of Dongting Lake-grown Miscanthus lutarioriparius biomass: A comprehensive quality analysis and bioproduct application study

Miscanthus lutarioriparius grown in Dongting Lake has an annual biomass yield potential of 1 million tons. However, with the shutdown of its previous utilization for paper-making, abandoning this huge amount of biomass has caused serious economic, ecological, and social problems. Constructing an industrial cluster to continuously convert biomass into various bioproducts is a win-win measure to address this dilemma. With the increasing confirmation of the importance of biomass quality affecting the conservation process, fully understanding the biomass characteristics of Dongting Lake-grown M. lutarioriparius is crucial for building a scientific industrial cluster. The present work is designed to explore the variation in biomass quality across the entire Dongting Lake area. Results show that the biomass contented with Cd, Mn, Zn, and Cr has significant geographical differences, with a general trend of Southern Dongting Lake-grown biomass having a higher concentration than that from Eastern and Western Dongting Lake areas. Moreover, significant differences are found in terms of biomass ash content, lignin content, and the degree of polymerization of cellulose (DP). The biomass with low ash content is generally from the entire Eastern Dongting Lake area and the northern part of the Western Dongting Lake area. Virtually all Western Dongting Lake-grown biomass has a low lignin content (approximately 18 %). Regarding the spatial variation of DP, Eastern Dongting Lake-grown biomass has a higher DP (average at 585.33) than that in Southern (575.15) and then Western Dongting Lake (529.16). Based on these quality indicators, the biomass production potentials for bioethanol, biochar, and xylo-oligosaccharide were calculated and visualized. Results show that biomass from almost the entire Western and Eastern Dongting Lake area is suitable for bioethanol and xylo-oligosaccharide production, while biomass from the Southern Dongting Lake area for biochar production. These results provide scientific guidance for the future utilization of Dongting Lake-grown M. lutarioriparius biomass.

Land Cover Classification of SAR Based on 1DCNN-MRF Model Using Improved Dual-Polarization Radar Vegetation Index

Accurate land cover classification (LCC) is essential for studying global change. Synthetic aperture radar (SAR) has been used for LCC due to its advantage of weather independence. In particular, the dual-polarization (dual-pol) SAR data have a wider coverage and are easier to obtain, which provides an unprecedented opportunity for LCC. However, the dual-pol SAR data have a weak discrimination ability due to limited polarization information. Moreover, the complex imaging mechanism leads to the speckle noise of SAR images, which also decreases the accuracy of SAR LCC. To address the above issues, an improved dual-pol radar vegetation index based on multiple components (DpRVIm) and a new LCC method are proposed for dual-pol SAR data. Firstly, in the DpRVIm, the scattering information of polarization and terrain factors were considered to improve the separability of ground objects for dual-pol data. Then, the Jeffries-Matusita (J-M) distance and one-dimensional convolutional neural network (1DCNN) algorithm were used to analyze the effect of difference dual-pol radar vegetation indexes on LCC. Finally, in order to reduce the influence of the speckle noise, a two-stage LCC method, the 1DCNN-MRF, based on the 1DCNN and Markov random field (MRF) was designed considering the spatial information of ground objects. In this study, the HH-HV model data of the Gaofen-3 satellite in the Dongting Lake area were used, and the results showed that: (1) Through the combination of the backscatter coefficient and dual-pol radar vegetation indexes based on the polarization decomposition technique, the accuracy of LCC can be improved compared with the single backscatter coefficient. (2) The DpRVIm was more conducive to improving the accuracy of LCC than the classic dual-pol radar vegetation index (DpRVI) and radar vegetation index (RVI), especially for farmland and forest. (3) Compared with the classic machine learning methods K-nearest neighbor (KNN), random forest (RF), and the 1DCNN, the designed 1DCNN-MRF achieved the highest accuracy, with an overall accuracy (OA) score of 81.76% and a Kappa coefficient (Kappa) score of 0.74. This study indicated the application potential of the polarization decomposition technique and DEM in enhancing the separability of different land cover types in SAR LCC. Furthermore, it demonstrated that the combination of deep learning networks and MRF is suitable to suppress the influence of speckle noise.

Mapping Paddy Rice Planting Area in Dongting Lake Area Combining Time Series Sentinel-1 and Sentinel-2 Images

Accurate and timely acquisition of cropping intensity and spatial distribution of paddy rice is not only an important basis for monitoring growth and predicting yields, but also for ensuring food security and optimizing the agricultural production management system of cropland. However, due to the monsoon climate in southern China, it is cloudy and rainy throughout the year, which makes it difficult to obtain accurate information on rice cultivation based on optical time series images. Conventional image synthesis is prone to omission or redundancy of spectral and temporal features that are potentially important for rice-growth identification, making it difficult to determine the optimal features for high-precision mapping of paddy rice. To address these issues, we develop a method to granulate the effective use interval of classification features by extracting phenological signatures of rice to obtain cost-effective and highly accurate mapping results. Two steps are involved in this method: (1) analyzing the information on various features (spectra, polarization, and seasonal regularity) to identify three key phenological periods throughout the lifespan of paddy rice; (2) identifying the features with the highest class separation between paddy rice, non-paddy crops, and wetlands under different phenological stages; and (3) removing redundant features to retain the optimal feature combinations. Subsequently, the obtained feature sets are used as input data for the random forest classifier. The results showed that the overall accuracy of the identified rice results was 95.44% with F1 scores above 93% for both single- and double-cropping rice. Meanwhile, the correlation coefficient of our mapped rice area compared with the official statistics of rice area at county and district levels was 0.86. In addition, we found that combining Sentinel-1 and Sentinel-2 images for rice recognition was better than using Sentinel-1 or Sentinel-2 alone, and the classification accuracy was improved by 5.82% and 2.39%, which confirms that the synergistic Sentinel-1 and Sentinel-2 data can effectively overcome the problem of missing optical images caused by clouds and rain. Our study demonstrates the potential of distinguishing mixed rice-cropping systems in subtropical regions with fragmented rice-field distribution in a cloudy and rainy environment, and also provides a basis for the rational layout of rice production and improvement of cultivation systems.

A Self-Adaptive Thresholding Approach for Automatic Water Extraction Using Sentinel-1 SAR Imagery Based on OTSU Algorithm and Distance Block

As an indispensable material for animals, plants and human beings, obtaining accurate water body information rapidly is of great significance to maintain the balance of ecosystems and ensure normal production and the life of human beings. Due to its independence of the time of day and the weather conditions, synthetic aperture radar (SAR) data have been increasingly applied in the extraction of water bodies. However, there is a great deal of speckle noise in SAR images, which seriously affect the extraction accuracy of water. At present, most of the processing methods are filtering methods, which will cause the loss of detailed information. Based on the characteristic of side-looking SAR, this paper proposed a self-adaptive thresholding approach for automatic water extraction based on an OTSU algorithm and distance block. In this method, the whole images were firstly divided into uniform image blocks through a distance layer which was produced by the distance to the orbit. Then, a self-adaptive processing was conducted for merging blocks. The OTSU algorithm was used to obtain a threshold for classification and the Jeffries–Matusita (JM) distance was calculated with the classification result. The merge processing continued until the separability of image blocks reached the maximum. Subsequently, we started from the next block to repeat the merger, and so on until all blocks were processed. Ten study areas around the world and the local Dongting Lake area were applied to test the feasibility of the proposed method. In comparison with five other global threshold segmentation algorithms such as the traditional OTSU, MOMENTS, MEAN, ISODATA and MINERROR, the proposed method obtains the highest overall accuracy (OA) and kappa coefficient (KC), while this approach also demonstrates greater robustness in the analysis of time series. The findings of this study offer an effective method to improve water detection accuracy as well as reducing the influence of speckle noise and retaining details in the image.