Search Results (63)

Grounded in the theoretical and methodological frameworks of landscape character identification from the European Landscape Map (LANMAP) and landscape character assessment (LCA), this study developed an AI-based tool for landscape character analysis to classify the Jianghan Plain’s landscape more effectively. The proposed method leveraged a deep learning model, the artificial intelligence-based landscape character (AI-LC) classifier, along with specific naming and coding rules for the unique landscape character of the Jianghan Plain. Experimental results showed a significant improvement in classification accuracy, reaching 89% and 86% compared to traditional methods. The classifier identified 10 macro-level and 18 meso-level landscape character types within the region, which were further categorized into four primary zones—a lake network river basin, a hillfront terrace, surrounding mountains, and a lake network island hill—based on natural and social features. These advancements contributed to the theoretical framework of landscape character assessment, offering practical insights for landscape planning and conservation while highlighting AI’s transformative potential in environmental research and management. Full article

The ecological protection of cultivated land is crucial for advancing high-quality agricultural development. This study analyzes the impact of agricultural socialization services on the ecological conservation of farmland, focusing on the reduction of chemical fertilizers and pesticides among rice farmers in the Jianghan Plain area. Utilizing data from 743 farmer household surveys conducted in 2023, the findings reveal that agricultural socialization services significantly encourage farmers to reduce chemical input usage. For every 1% increase in the level of agricultural social services, the average fertilizer use per hectare will decrease by 14% and the average pesticide use per hectare will decrease by 16.4%. The study identifies scale operation, factor substitution, and alleviation of capital constraints as mediating factors enhancing the efficacy of these services. Furthermore, heterogeneity analysis indicates that these services are more effective in reducing chemical inputs among large-scale and newer-generation farmers compared to their small-scale and older counterparts. Additionally, technology-intensive socialized services exhibit a stronger impact on reducing chemical inputs than labor-intensive services. Full article

The early and accurate mapping of winter canola is essential in predicting crop yield, assessing agricultural disasters, and responding to food price fluctuations. Although some methods have been proposed to map the winter canola at the flowering or later stages, mapping winter canola planting areas at the early stage is still challenging, due to the insufficient understanding of the multi-source remote sensing features sensitive for winter canola mapping. The objective of this study was to evaluate the potential of using the combination of optical and synthetic aperture radar (SAR) data for mapping winter canola at the early stage. We assessed the contributions of spectral features, backscatter coefficients, and textural features, derived from Sentinel-2 and Sentinel-1 SAR images, for mapping winter canola at early stages. Random forest (RF) and support vector machine (SVM) classification models were built to map winter canola based on early-stage images and field samples in 2017 and then the best model was applied to corresponding satellite data in 2018–2022. The following results were obtained: (1) The red edge and near-infrared-related spectral features were most important for the mapping of early-stage winter canola, followed by VV (vertical transmission, vertical reception), DVI (Difference vegetation index), and GOSAVI (Green Optimized Soil Adjusted Vegetation Index); (2) based on Sentinel-1 and Sentinel-2 data, winter canola could be mapped as early as 130 days prior to ripening (i.e., early overwinter stage), with the F-score over 0.85 and the OA (Overall Accuracy) over 81%; (3) adding Sentinel-1 could improve the OA by about 2–4% and the F-score by about 1–2%; and (4) based on the classifier transfer approach, the F-scores of winter canola mapping in 2018–2022 varied between 0.75 and 0.97, and the OAs ranged from 79% to 86%. This study demonstrates the potential of early-stage winter canola mapping using the combination of Sentinel-2 and Sentinel-1 images, which could enable the large-scale early mapping of canola and provide valuable information for stakeholders and decision makers. Full article

The carbon storage capacity of terrestrial ecosystems serves as a crucial metric for assessing ecosystem health and their resilience to climate change. By evaluating the effects of land use alterations on this storage, carbon management strategies can be improved, thereby promoting carbon reduction and sequestration. While county-level cities are pivotal to ecological conservation and high-quality development, they often face developmental challenges. Striking a balance between economic growth and meeting peak carbon emissions and carbon neutrality objectives is particularly challenging. Consequently, there is an urgent need to bolster research into carbon storage management. The study focuses on Jianli City, employing the InVEST model and land use data to examine the response patterns of land use changes and terrestrial system carbon storage from 2000 to 2020. Using the PLUS model, the study simulated the land use and carbon storage in Jianli City for the year 2035 under three scenarios: Natural Development scenario, Urban Expansion scenario, and Ecology and food security scenario. Our findings indicate the following: (1) Between 2000 and 2020, significant shifts in land use were observed in Jianli City. These changes predominantly manifested as the interchange between Cropland and Water areas and the enlargement of impervious surfaces, leading to a decrease of 691,790.27 Mg in carbon storage. (2) Under the proposed scenarios—Natural Development scenario, Urban Expansion scenario, and Ecology and food security scenario—the estimated carbon storage capacities in Jianli City were 39.95 Tg, 39.90 Tg, and 40.14 Tg, respectively. When compared with the 2020 data, all these estimates showed an increase. In essence, our study offers insights into optimizing land use structures from a carbon storage standpoint to ensure stability in Jianli’s carbon storage levels while mitigating the risks associated with carbon fixation. This has profound implications for the harmonious evolution of regional eco-economies. Full article

The study of the spatio-temporal distribution and evolution trends of water resources in large regions plays an important role in the study of regional water resource planning, regional economic and social development, and water disasters. In this study, a Landsat multi-index relationship and water probability thresholding method is developed based on the Google Earth Engine (GEE) platform, which can support the integration of multiple Landsat satellites. The algorithm jointly combines multiple remote sensing metrics along with the calculation of water probability to produce an interannual water body product for the Jianghan Plain on a 20-year time series. The results indicate that the Landsat multi-index relationship algorithm used in this study has high accuracy in extracting long-term water bodies in extensive, flat terrain areas such as the Jianghan Plain, with an overall accuracy (OA) of 97.23%. By analyzing the water body products and landscape patterns, we have identified the following features: (1) From 2002 to 2021, the changes in river water bodies in the Jianghan Plain were relatively small, and some lakes experienced a shrinkage in area. Overall, there is a strong correlation between water distribution and precipitation. (2) The complexity index of water bodies shows a strong negative correlation with effective irrigation area and population, indicating a strong mutual influence between water bodies and socio-economic activities. (3) Through the study of the distribution characteristics of built-up areas and the water system, it was found that for large rivers, the larger the size of the river, the more built-up areas are nearby. Most extensive built-up areas are located near large rivers. This study contributes to providing methods and data support for urban planning, water resource management, and disaster research in the Jianghan Plain. Full article

The income effect of rice–crayfish co-culture technology (RCT) is directly related to rate of adoption of farmers and the process of China’s green development of agriculture. The aim of this study is to explore the income effect and income growth mechanism of rice–crayfish co-culture technology from the perspective of continuous adoption. With the treatment effect model (TEM), this paper empirically analyzes the income effect and income-generating mechanisms of RCT using field survey data from 736 farmers in the Jianghan Plain. As a result of this study, it was discovered that RCT will increase farmers’ net agricultural income by RMB 83,430 if they continue to adopt it. Further examinations indicate that the optimal adoption period for RCT is four and a half years. Additionally, it has also been shown that non-farm employment positively moderates the relationship between continuous adoption of RCT and net agricultural income. Farmers who participate in non-farm employment and continue to adopt the RCT will experience an increase in net agricultural income by RMB 104,510. Therefore, our results suggest that it is necessary to encourage farmers to continuously adopt RCT and actively participate in non-farm employment to enhance the income effect of RCT. Full article

With the development of industry and agriculture, the level of organic pollutants in groundwater exceeds the standard in some parts of the transition zone of the Jianghan Plain–Dabie Mountain area. To investigate the ability of low-permeability layered clay soil in the study area to hinder the migration of organic macromolecular pollutants, the traditional tracer fluorescein sodium was used to represent organic macromolecular pollutants. The adsorption and migration behavior of organic macromolecular pollutants in the layered soil were explored through indoor experiments. Additionally, a one-dimensional soil column solute transport model was established for the study area using HYDRUS-1D to obtain the dispersivities and dispersion coefficients of organic macromolecular pollutants in layered clay soil. The results showed that the breakthrough duration of sodium fluorescein was up to 116 days in silty clay soil, while the breakthrough duration in sandy sub-sandy soil was only 2.6 days. The dispersion coefficient of organic macromolecular pollutants was only 0.0038 cm²/d in silty clay soil, while the dispersion coefficient was up to 4.724 cm²/d in sandy sub-sandy soil. The dispersion coefficient decreased with the increasing clay fraction of the soil. Compared with homogeneous soil, the dispersivity of organic macromolecular pollutants in clayed soil decreased, and the dispersion coefficient also changed. It indicates that the layered clay soil in the study area effectively hinders the downward migration of organic macromolecular pollutants due to its low permeability and pollutant adsorption capacity. Simultaneously, the lateral transport of water at different soil interfaces in layered soil prolongs the time for organic macromolecular pollutants to reach the underlying aquifer. Low-permeability clay soil may act as a short-term barrier to the migration of organic pollutants to deeper soil and groundwater in the study area. This study provides data support and a theoretical basis for future pollution prevention and control in the Jianghan Plain–Dabie Mountain area. Full article

The lakes of Jianghan Plain, as an important component of the water bodies in the middle and lower reaches of the Yangtze River plain, have made significant contributions to maintaining the ecological health and promoting the sustainable development of the Jianghan Plain. However, there is a relatively limited understanding regarding the trends of lake area change for different types of lakes and their dominant factors over the past three decades in the Jianghan Plain. Based on the Google Earth Engine (GEE) platform, combined with the water body index method, the changes in area of three different types of lakes (area > 1 km²) in the Jianghan Lake Group from 1990 to 2020 were extracted and analyzed. Additionally, the Partial least squares structural equation model (PLS-SEM) was utilized to analyze the driving factors affecting the changes in water body area of these lakes. The results show that from 1990 to 2020, the area of the lakes of the wet season and level season exhibited a decreasing trend, decreasing by 893.1 km² and 77.9 km², respectively. However, the area of dry season lakes increased by 59.27 km². The areas of all three types of lakes reached their minimum values in 2006. According to the PLS-SEM results, the continuous changes in the lakes’ area are mainly controlled by environmental factors overall. Furthermore, human factors mainly influence the mutation of the lakes’ area. This study achieved precise extraction of water body areas and accurate analysis of driving factors, providing a basis for a comprehensive understanding of the dynamic changes in the lakes of Jianghan Plain, which is beneficial for the rational utilization and protection of water resources. Full article

The rice–crayfish rotation system (RCR), originating in the Jianghan Plain, is developing rapidly in various regions of China and has been characterized by unbalanced regional development, which has also led to widespread concerns and discussion on its environmental impacts and sustainability. This study selects representative RCR production areas in the Jianghan Plain, including Jianli, Qianjiang, Shishou, Shayang, Gong’an and Honghu, to analyze resource inputs, resource utilization efficiency, environmental impacts and sustainability by employing the emergy analysis method. Our analysis of Jianli, Honghu, Qianjiang, Gong’an, Shishou and Shayang reports total emergy inputs ranging from 6.46 × 10¹⁶ to 8.25 × 10¹⁶, with renewable rates between 78.38% and 84.34%. Shishou leads in the unit emergy value (5.58 × 10⁻¹) and the emergy yield ratio (5.30). The sustainability evaluation finds that the environmental loading ratio is from 0.19 to 0.28 and the emergy index for sustainable development varies between 1.27 and 3.00. This analysis indicates that the southern regions have higher inputs and efficiency, with southeastern areas showing lower environmental impact and higher sustainability. We also underscore the impact of non-renewable resources on environmental outcomes and sustainability, suggesting tailored development strategies for the rice–crayfish rotation system’s optimization and sustainable growth. Full article

Geogenic arsenic (As)-rich groundwater poses a significant environmental challenge worldwide, yet our understanding of the interplay between dissolved organic matter (DOM) transformation and arsenic mobilization during microbial sulfate reduction remains limited. This study involved microcosm experiments using As-rich aquifer sediments from the Singe Tsangpo River basin (STR) and Jianghan Plain (JHP), respectively. The findings revealed that microbial sulfate reduction remarkably increased arsenic mobilization in both STR and JHP sediments compared to that in unamended sediments. Moreover, the mobilization of As during microbial sulfate reduction coincided with increases in the fluorescence intensity of two humic-like substances, C2 and C3 (R = 0.87/0.87 and R = 0.73/0.66 in the STR and JHP sediments, respectively; p < 0.05), suggesting competitive desorption between DOM and As during incubation. Moreover, the transformations in the DOM molecular characteristics showed significant increases in CHOS molecular and low-O/C-value molecular intensities corresponding to the enhancement of microbial sulfate reduction and the possible occurrence of methanogenesis processes, which suggests a substantial bioproduction contribution to DOM components that is conducive to As mobilization during the microbial sulfate reduction. The present results thus provide new insights into the co-evolution between As mobilization and DOM transformations in alluvial aquifer systems under strong microbial sulfate reduction conditions. Full article

The rice–crayfish co-culture system, a representative of Agri-aqua food systems, has emerged worldwide as an effective strategy for enhancing agricultural land use efficiency and boosting sustainability, particularly in China and Southeast Asia. Despite its widespread adoption in China’s Jianghan Plain, the exact spatiotemporal dynamics and factors influencing this practice in this region are yet to be clarified. Therefore, understanding the spatiotemporal dynamics and influencing factors of the rice–crayfish fields (RCFs) is crucial for promoting the rice–crayfish co-culture system, and optimizing land use policies. In this study, we identified the spatial distribution of RCF using Sentinel-2 images and land use spatiotemporal data to analyze its spatiotemporal dynamics during the period of 2016–2020. Additionally, we used the Multiscale Geographically Weighted Regression model to explore the key factors influencing RCF’s spatiotemporal changes. Our findings reveal that (1). the RCF area in Jianghan Plain expanded from 1216.04 km² to 2429.76 km² between 2016 and 2020, marking a 99.81% increase. (2). RCF in Jianghan Plain evolved toward a more contiguous and clustered spatial pattern, suggesting a clear industrial agglomeration in this area. (3). The expansion of the RCFs was majorly influenced by its landscape and local agricultural conditions. Significantly, the Aggregation and Landscape Shape Indexes positively impacted this expansion, whereas proximity to rural areas and towns had a negative impact. This study provides a solid foundation for promoting the rice–crayfish co-culture system and sustainably developing related industries. To ensure the sustainable development of rice–crayfish co-culture industries in Jianghan Plain, we recommend that local governments optimize the spatial layout of rural settlements, improve transportation infrastructure, and enhance regional agricultural water sources and irrigation system construction, all in line with the national strategy of rural revitalization and village planning. Additionally, promoting the concentration and contiguity of RCF through land consolidation can achieve efficient development of these industries. Full article

Both larvae and adults of the Henosepilachna vigintioctopunctata feed on leaves of potatoes, tomatoes, and eggplants. Given the variation in planting times of host plants in the Jianghan Plain, host switching between larvae and adults of H. vigintioctopunctata is inevitable to ensure continuous food availability. We evaluated the effect of consistent versus diverse larval and adult host plant feeding experience on growth performance, fecundity, longevity, and feeding preferences of H. vigintioctopunctata through match-mismatch experiments. Host plant quality significantly influences larval development and adult reproduction. Potatoes are identified as the optimal host plant for H. vigintioctopunctata, whereas eggplants significantly negatively affect the adult fecundity. Adult stage host feeding experience determines the fecundity of H. vigintioctopunctata, irrespective of the larval feeding experience. The fecundity of H. vigintioctopunctata adults on eggplant leaves remains significantly lower than that observed on potato leaves. Similarly, adult H. vigintioctopunctata demonstrate a preference for consuming potato leaves, irrespective of the larval feeding experience. Although host switching between larval and adult stages offers lesser benefits for the performance of herbivorous insects compared to a consistent diet with potato leaves, it maintains H. vigintioctopunctata population continuity amidst shortages of high-quality potato hosts. Full article

Southern China, one of the traditional rice production bases, has experienced significant declines in the area of rice paddy since the beginning of this century. Monitoring the rice cropping area is becoming an urgent need for food security policy decisions. One of the main challenges for mapping rice in this area is the quantity of cloud-free observations that are vulnerable to frequent cloud cover. Another relevant issue that needs to be addressed is determining how to select the appropriate classifier for mapping paddy rice based on the cloud-masked observations. Therefore, this study was organized to quickly find a strategy for rice mapping by evaluating cloud-mask algorithms and machine-learning methods for Sentinel-2 imagery. Specifically, we compared four GEE-embedded cloud-mask algorithms (QA60, S2cloudless, CloudScore, and CDI (Cloud Displacement Index)) and analyzed the appropriateness of widely accepted machine-learning classifiers (random forest, support vector machine, classification and regression tree, gradient tree boost) for cloud-masked imagery. The S2cloudless algorithm had a clear edge over the other three algorithms based on its overall accuracy in evaluation and visual inspection. The findings showed that the algorithm with a combination of S2cloudless and random forest showed the best performance when comparing mapping results with field survey data, referenced rice maps, and statistical yearbooks. In general, the research highlighted the potential of using Sentinel-2 imagery to map paddy rice with multiple combinations of cloud-mask algorithms and machine-learning methods in a cloud-prone area, which has the potential to broaden our rice mapping strategies. Full article

With the evolution of remote sensing, more data products concerning cropland distribution are becoming available. However, the accuracy and consistency across all datasets in crucial regions are inherently uncertain. We delved into the Middle Yangtze Plain, a complex and vital agricultural area with relatively high cultivation intensities in China. We used confusion matrices and consistency analysis to compare the accuracy and consistency of four multi-year cropland distribution data products. These include Global Land Analysis & Discovery Cropland Data (GLAD), Annual Global Land Cover (AGLC), the China Land Cover Dataset (CLCD), and China’s Annual Cropland Dataset (CACD). Key findings include the following: GLAD has the highest precision at 96.09%, the CLCD has the highest recall at 98.41%, and AGLC and CACD perform well in achieving a balance between precision and recall, with F1 scores of 90.30% and 90.74%, respectively. In terms of consistency, GLAD and the CLCD show inconsistency at 69.58%. When all four products unanimously classify a pixel as cropland, the identified cropland area closely corresponds to the statistical data reported in the yearbook. The Jianghan Plain holds the majority of cropland in the Middle Yangtze Plain, constituting 50.88%. From 2003 to 2019, the cropland area experienced fluctuating and ascending trends. Shangrao City witnessed the most notable rise in cropland area, with an increase of 323.0 km², whereas Wuhan City underwent the most substantial decline, amounting to 185.8 km². These findings contribute valuable insights into the precision and consistency of existing cropland distribution products, offering a foundation for further research. Full article

An extremely low hydraulic conductivity of cohesive soil causes a low transport rate of water and solute, with a time-consuming result, as we all know. Stable isotopes (δD and δ¹⁸O) and in situ monitoring systems of the data about soil water, rainfall, and groundwater were used to analyze the soil moisture migration pattern, using a conceptual model in the field test site, simulated by Hydrus 1D. The results show that multiple rainfalls’ accumulations can cause the water to recharge from soil moisture to micro-confined groundwater, gradually. The soil moisture dynamic change is composed of a dehydration period and absorption period; the cohesive soil water content below 5.0 m was affected by the micro-confined groundwater level and dehydrated in advance due to the level decline. The thick cohesive soil profile can be divided into a shallow mixing zone (0–2 m), steady zone (2–5 m), and deep mixing zone (5–15 m). The effective precipitation recharge was 234 mm and the average infiltration recharge coefficient (Rc) was 0.1389, but the water exchange between the cohesive soil moisture and groundwater was 349 mm in two hydrological years. This paper reveals the moisture migration and recharge pattern of low-permeability thick cohesive soil in a humid area with a micro-confined groundwater aquifer; this is of great significance for groundwater resources evaluation and environmental protection in humid climate plain areas. Full article