摘要：
<jats:p>Logistics services are integral to urban economic activity, and delving into the spatial distribution traits and evolutionary pathways of various kinds of logistics service node facilities (LSNF) is markedly valuable for understanding a city’s functional spatial makeup and refining the spatial layout of logistics services. This study quantitatively and qualitatively analyzes the spatial congregation and spreading characteristics of diverse LSNFs in Wuhan in 2011, 2014, 2017, and 2020, employing kernel density analysis, average nearest neighbor index, mean center, and distance distribution frequency, seeking to characterize the spatial evolution characteristics of LSNF, alongside examining the trends in distances to city cores, principal adjoining roads, and production and consumption sites. The following conclusions were made: (1) Between 2011 and 2020, various types of LSNFs in Wuhan experienced a pattern characterized by the noticeable coexistence of spatial expansion and agglomeration, particularly visible after 2014. The degree of agglomeration is classified in a descending order as follows: CWC, STN, PSN, and PDN. (2) An “absolute diffusion” phenomenon characterizes the distribution of distances between various kinds of LSNFs and city cores or neighboring roads, with the lion’s share of high-frequency distribution zones spreading beyond city cores by 5–10 km, and a majority of the LSNFs being situated within 1 km from adjacent roads. (3) While the LSNF collective exhibits a stronger tendency towards the consumption facet, it reflects a surrounding of industrial production sites on the production facet and locations of manufactured goods consumption on the consumption facet, followed by locations of agricultural product consumption and comprehensive consumption sites.</jats:p>
摘要：
The cluster patterns of features in map space represent a comprehensive reflection of individual feature geometric attributes and their spatial adjacency relationships. These patterns also embody spatial cognition results under the Gestalt principle. Describing non-linear spatial cluster patterns as effective regular structures is one of the fundamental tasks in deep learning for recognizing feature cluster patterns. In this study, based on the concept of texture co-occurrence matrices from regular gray-scale images, we utilized Voronoi diagrams to construct the tessellation structure of building polygons. Built upon the foundation of first-order texton co-occurrence matrices, we established three-dimensional texton co-occurrence matrices for building polygons, considered five attributes of building size, shape, orientation, and density, and encompassed 64 different combinations of second-order neighboring directions. This matrix concretizes the latent Gestalt spatial characteristics of building polygon clusters into a three-dimensional sparse matrix. It is then used as an input vector to construct a deep convolutional neural network for recognizing building polygon cluster patterns. Through adjustments and optimizations of neural network structure and strategies, along with validation through practical case studies and comparisons with other models, we have demonstrated the effectiveness of the second-order texton co-occurrence matrix in describing the characteristics of building polygon clusters.
摘要：
Climate-smart agriculture is guided by three main goals: increased productivity, enhanced resilience (climate change adaptation), and reduced emissions (climate change mitigation). Early mature crop varieties have been promoted to minimize the impact of climate change and extreme weather events on farming activities. This study examined the effects of adopting early mature rice varieties on agricultural productivity, climate change adaptation, and mitigation. Data came from a cross-sectional sample of 1396 rice farmers in Hubei, China. Productivity was measured via mean rice yield. Production risk (variance of yield) and downside risk (skewness of rice yield) were used as proxies for adaptation. Life cycle assessment was used to calculate the greenhouse gas emissions of rice production. Results indicated that adopting early maturing varieties significantly increased mean rice yield and reduced production risk, downside risk, and greenhouse gas emissions. Altogether, this study provided evidence that using early maturing varieties positively contributed to the three goals of climate-smart agriculture. Our findings provide insight into formulating future policies and programs promoting agricultural sustainability and climate resilience in China and other developing nations in the region.
摘要：
The rice -crayfish field (i.e., RCF), a recently emerged rice cultivation pattern, has experienced remarkable growth in China over the last decade due to its significant socioeconomic advantages. However, the impacts of expanding RCF areas on the regional -scale ecological environment, particularly concerning methane (CH4) emissions, remain unclear. A major obstacle in addressing this knowledge gap is the absence of accurate and upto-date spatial distribution information on RCF across years. Here, we selected Jianghan Plain which has the largest RCF area in China as the study area. First, we developed a phenology-based identification algorithm using Landsat-7/8 satellite data, which considered the distinctive flooding signatures of RCF during the rice fallow periods, to identify RCF at the regional scale. Second, we employed the DeNitrification-DeComposition (DNDC) model to simulate the CH4 fluxes of various rice cropping systems, including RCF, rice monoculture (RM), ricerapeseed rotation (RR), and rice -wheat rotation (RW). Finally, the effects of RCF expansion during 2014-2019 on regional CH4 emissions were analyzed by comparing six scenarios that simulated the conversion of different rice cropping systems to RCF. Results showed the phenology-based algorithm performed well in extracting RCFs, achieving an overall accuracy >92 % for all years based on 1025 RCF and 2096 non-RCF validation samples. RCF generated the least CH4 flux, followed by RM, RR, and RW. Moreover, shifting from traditional rice cropping systems to RCF reduced CH4 emissions across all cases, with mitigation rates ranging from 4.82 % to 21.85 %, indicating RCF's substantial CH4 mitigation potential. These findings significantly improve our understanding of the ecological effects of RCF cultivation, which is critical for advancing land use planning and decision -making for sustainable agricultural development in China. Our presented evaluation method of integrating the remote sensing mapping algorithm and DNDC model can be easily generalized for other crop types in other regions.
摘要：
Given the increased incidence of pluvial floods due to climate change and urbanization, the demand for highly efficient and accurate modeling within urban drainage systems has intensified, making machine learning and deep learning techniques increasingly popular. Nonetheless, these data-driven approaches face challenges in adequately capturing and interpreting dynamic process-evolving features, especially the spatiotemporal effects emanating from manholes during urban waterlogging events. To address these issues, this study proposes a general framework that extracts the spatiotemporal effects using the dynamic spatial Durbin model, integrates such effects with four machine learning models (i.e., artificial neural network, Bayesian neural network (BNN), light gradient boosting machine, and long short-term memory network), and clarifies decision-making processes of the best model by employing the Shapley Additive Explanations (SHAP) method. The results indicate that (1) the BNN with spatiotemporal effects (BNNST) not only outperforms other benchmark models but also provides accurate forecasts with quantifiable uncertainties; (2) compared to the original model, spatiotemporal effects enhance the models' understanding of urban flooding dynamics, thereby improving predictive precision; (3) spatiotemporal effects comprise roughly 14 % of the contributions to the BNNST's output, as interpreted by SHAP-based explanations; (4) incorporating interpretability into the BNN technique underscores the trustworthiness of the explanations at varying confidence levels, thereby deepening the understanding of decision-making processes.
作者机构：
[Chen, GL; Chen, Guolei; Ma, Taijia; Li, Lianlian; Zhang, Jisha] Guizhou Normal Univ, Sch Geog & Environm Sci, Guiyang 550025, Peoples R China.;[Zhang, Chunyan; Luo, Jing] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.;[Zhang, Chunyan; Luo, Jing] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.;[Zhang, Chunyan; Luo, Jing] Hubei High Qual Dev Res Inst, Res Off Hubei Prov Peoples Govt, Wuhan, Peoples R China.;[Zhang, Chunyan; Luo, Jing] Cent China Normal Univ, Wuhan, Peoples R China.
通讯机构：
[Chen, GL ] G;Guizhou Normal Univ, Sch Geog & Environm Sci, Guiyang 550025, Peoples R China.
关键词：
public health;development;entropy method;western China
摘要：
The public health level in a country is closely related to national development and quality of life. In order to appraise the level of health services in the western region of China, panel data of 124 prefecture-level units covering the period 2011 to 2021 was used together with a health evaluation index system based on four dimensions: quality of life, environmental situation, the level of health services and longevity. To assess this, we used entropy weights, standard deviation and coefficient of variation together with the geographical detector model that measures the stratified spatial heterogeneity. The results show that although public health services have improved overall, the various dimensions are still not balanced as longevity did not match up everywhere. While the developmental level of the various health dimensions presents a pattern of a relatively smooth increasing gradient in the west-central- east direction, the situation with respect to the north-centralsouth is more uneven with both ups and downs. However, a trend of continuous enhancement of all health dimensions was found with a significant positive correlation of spatial clustering, with hotspots and 'sub-hotspots' contracting from north to south, while coldspots and 'sub-coldspots' expanded from west to east. This can be seen as the result of multiple factors, with the level of urbanization and economic level as the dominant factors and government guidance, agglomeration capacity and industrial structure being auxiliary.
摘要：
Accurate spatio-temporal information on rice cropping patterns is vital for predicting grain production, managing water resource and assessing greenhouse gas emissions. However, current automated mapping of rice cropping patterns at regional scale is heavily constrained by insufficient training samples and frequent cloudy weathers in major rice-producing areas. To tackle this challenge, we proposed a Phenology domain Optical-SAR feature inTegration method to Automatically generate single (SC-Rice) and double cropping Rice (DC-Rice) sample (POSTAR) for efficient and refined rice mapping. POSTAR includes three major steps: (1) generating a potential rice map using a phenology- and object-based classification method with optical data (Sentinel-2 MSI) to select candidate rice samples; (2) employing K-means to identify SC- and DC-Rice candidate samples according to unique SAR-based (Sentinel-1 SAR) phenological features; (3) implementing a two-step refinement strategy to filter high-confidence SC- and DC-Rice samples, maintaining a balance between intraclass phenological variance and sample purity. Test areas selected for validation include the Dongting Lake plain and Poyang Lake plain in South China, as well as Fujin county located in the Sanjiang plain of North China. POSTAR proved effective in producing reliable SC- and DC-Rice samples, achieving a high spectral correlation similarity (>0.85) and low dynamic time wrapping distance (<8.5) with field samples. Applying POSTAR-derived samples to random forest classifier yielded an overall accuracy of 89.6%, with F1 score of 0.899 for SC-Rice and 0.938 for DC-Rice in the Dongting Lake plain. Owing to the incorporation of knowledge-based optical and SAR phenological features, POSTAR exhibited strong spatial transferability, achieving an overall accuracy of 96.0% in the Poyang Lake plain and 97.8% in the Fujin county. These results demonstrated the effectiveness of the POSTAR method in accurately mapping rice cropping patterns without extensive field visits, providing valuable insights for crop monitoring in large, diverse, and cloudy regions through the integration of optical and SAR data.
作者机构：
[Wang, Yingying; Li, Xiangqiang] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.;[Wang, Yingying; Li, Xiangqiang] Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Hubei, Peoples R China.;[Huang, Ying] Univ Elect Sci & Technol China, Zhongshan Inst, Zhongshan, Guangdong, Peoples R China.
通讯机构：
[Huang, Y ] U;[Li, XQ ] C;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.;Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Hubei, Peoples R China.;Univ Elect Sci & Technol China, Zhongshan Inst, Zhongshan, Guangdong, Peoples R China.
摘要：
An in-depth study of the mechanisms governing the generation, evolution, and regulation of differences in tourism economics holds significant value for the rational utilization of tourism resources and the promotion of synergistic tourism economic development. This study utilizes mathematical statistical analysis and GIS spatial analysis to construct a single indicator measure and a comprehensive indicator measure to analyze tourism-related data in the research area from 2004 to 2019. The main factors influencing the spatial and temporal differences in the tourism economy are analyzed using two methods, namely, multiple linear regression and geodetector. The temporal evolution, overall differences and differences within each city group fluctuate downwards, while the differences between groups fluctuate upwards. Domestic tourism economic differences contribute to over 90% of the overall tourism economic differences. Spatial divergence, the proportion of the tourism economy accounted for by spatial differences is obvious, the comprehensive level of the tourism economy can be divided into five levels. The dominant factors in the formation of the pattern of spatial and temporal differences in the tourism economy are the conditions of tourism resources based on class-A tourist attractions and the level of tourism industry and services based on star hotels and travel agencies. This study addresses the regional imbalance of tourism economic development in city clusters and with the intent of promoting balanced and high-quality development of regional tourism economies.
作者：
Zhao, Ying;Yi, Jun;Yao, Rongjiang;Li, Fei;Hill, Robert Lee;...
期刊：
Vadose Zone Journal,2024年23(4):e20367- ISSN：1539-1663
通讯作者：
Zhao, Y;Yao, RJ
作者机构：
[Zhao, Ying] Ludong Univ, Coll Resources & Environm Engn, Yantai 264025, Peoples R China.;[Zhao, Ying] Univ Saskatchewan, Global Inst Water Secur, Saskatoon, SK, Canada.;[Yi, Jun] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.;[Yao, Rongjiang] Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China.;[Li, Fei] Chinese Acad Agr Sci, Grassland Res Inst, Hohhot, Peoples R China.
通讯机构：
[Yao, RJ ] C;[Zhao, Y ] L;Ludong Univ, Coll Resources & Environm Engn, Yantai 264025, Peoples R China.;Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China.
摘要：
Preferential flow (PF) processes are governed by subsurface soil structures at various scales. Still, model validation and mechanistic understanding of PF are very lacking. We hypothesize that PF at hillslope and larger scales cannot be described and quantified when neglecting small-scaled spatially variable processes and simplifying the model dimensionality. The objective was to learn from comparing simulation results of multidimensional (1D, 2D, and 3D) and multiscale (pedon, catena, and catchment) modeling approaches with comprehensive datasets, and so as to evaluate PF simulations based on the Richards' equation (solved by the HYDRUS software). Results showed limited alignment between 1D simulations and soil moisture data, mainly affected by vertical changes in porosity, permeability, and precipitation features. 2D and 3D simulations outperformed 1D models. 3D simulations provided satisfactory description of PF dynamics at the pedon scale, considering accurate representations of soil and bedrock structures for three dimensions (vertical, horizontal, and surrounding area). In 2D simulations at the pedon scale, models incorporating dual-porosity and anisotropy of soils yielded more accurate predictions of water dynamics than single-porosity and isotropic models. Furthermore, the application of 2D simulation at the catena scale identify PF pathways owing to the enhanced representation of the hydraulic connectivity between different locations along the slope. The results confirmed the significance of multidimensional and multiscale modeling approaches for PF simulations in hillslope hydrology. Considering the complexity and parameterization of 2D and 3D "bottom-up" physically based models in representing spatial variability within and between soil profiles and/or underlying bedrock geology, the results contribute to creating a modeling framework applicable to identify the PF processes and thus their implications in managing water resources. The 3D model was better than 2D model to detect the preferential flow. A dual-porosity or anisotropy model produced more accurate predictions than a single-porosity or isotropy model. A model domain that considered fractured bedrock performed better than without it.
摘要：
Although deep learning (DL) models, especially long-short-term memory (LSTM), demonstrate greater accuracy than process-based models in rainfall-runoff simulation, the predictions from process-based models are more physical than DL models. The main reason is that DL models have almost no process understanding capabilities like process-based models beyond their fitting capability. In this study, we developed a process-driven DL model under a unified DL architecture to improve the process awareness of DL models. To implement the model, a conceptual hydrological model (EXP-HYDRO) is implanted into a recurrent neural network (RNN) cell as a process driver for providing multi-sub-process variables related to the runoff process, and an Entity-Aware LSTM (EA-LSTM) cell is incorporated as a post-processor layer, resulting in the Process-driven RNN-EA-LSTM (PRNNEA-LSTM). Under the assistance of the process driver, the model performance of PRNN-EA-LSTM on the 531 catchments from the Catchment Attributes and Meteorology for Large-sample Studies dataset is more robust than the pure DL model, and better than using only EXP-HYDRO as the input of EA-LSTM (i.e., EXP-HYDRO-EALSTM). Specifically, the median Nash-Sutcliffe efficiency (NSE) of PRNN-EA-LSTM in local and regional simulation is 0.03 and 0.02 higher than LSTM and 0.01 higher than EXP-HYDRO-EA-LSTM. Additionally, PRNN-EALSTM significantly enhances the low flow simulations and reduces the catchments number with negative NSE. This study demonstrates that process-based models can help DL models better represent the rainfall-runoff relationship under a unified architecture. Consequently, integrating the adaptability of process-based models into the DL architecture is anticipated to bolster the process understanding capabilities of DL models.
摘要：
Land cover mapping is crucial for natural resource assessment, urban planning, and sustainable development. Land cover nomenclature often includes two or three hierarchical levels with tree-like hierarchical structures. This study aims to explore these hierarchical relationships and the potential of hierarchical semantic segmentation for land cover mapping. We propose a hierarchical semantic segmentation architecture by taking advantage of dual U-shaped network, named as HierU-Net. The coarse-level result is ingested to the fine-level segmentation functioned as soft constraints. The propagation of error will not be certain. Moreover, we employ a multitask loss function weighted by homoscedastic uncertainty to optimize the training. To evaluate the performance of the proposed method, we create a hierarchical semantic segmentation dataset (HierToulouse), which contains 11 528 samples, including images and land cover labels at two hierarchical levels. The experiments demonstrate that the proposed approach is capable of achieving accurate land cover segmentation at both coarse and fine levels, with segmentation results surpassing those obtained using the flat method.
通讯机构：
[Wu, TN ] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
关键词：
Parent materials;Soil water -retention curve;Water -stable aggregates;Red soil
摘要：
The parent materials play an important role in soil hydrologic properties. However, in subtropical hilly areas with complex geological conditions, it appears that there is a lack of full understanding about the effect of parent material on soil water-holding and erosion resistance, which can be helpful for agricultural production and conservation of soil and water. In this study, five red soils developed from shale (Ds), quartz sandstone (Dqs), argillaceous nodular limestone (Danl), argillaceous limestone (Dal), and limestone conglomerate (Dlc) in subtropical China were selected. Soil properties, soil water-retention curves (SWRCs), water-stable aggregate fractions, and soil erodibility factor (K) were tested and calculated. The results showed that there are significant differences in soil texture among soils developed from different parent materials, soils with higher clay content have stronger water-holding capacity, and the average water-holding capacity of the five soils followed the order Dal > Danl > Ds > Dlc > Dqs. Furthermore, the erosion resistance of soil is closely related to the clay content and the stability of soil aggregates, and the sequence of average K-value among the five soil types is as follows: Danl > Dal > Dlc > Ds > Dqs. Partial least squares regression revealed that the stability of aggregates has a more significant influence on soil erodibility than the clay content. Therefore, soils with higher mean weight diameter (MWD) and geometric mean diameter (GMD) are more resistance to erosion. This paper evaluated the distinctions in basic properties and hydraulic properties between different parent materials under similar climatic conditions, elevations and vegetation in subtropical hilly area of Southern China, which can serve as a scientific foundation for soil and water conservation in the environments characterized by complex geological conditions.
摘要：
The Northern Hemisphere mid-latitudes, with large human populations and terrestrial carbon sinks, have a high demand for and dependence on water resources. Despite the growing interest in vegetation responses to drought under climate change in this region, our understanding of changes in the relationship between vegetation growth and water availability (referred to as Rvw) remains limited. Here, we aim to explore the Rvw and its drivers in the Northern Hemisphere mid-latitudes between 1982 and 2015. We used the satellite-derived normalized difference vegetation index (NDVI) and the fine-resolution Palmer drought severity index (PDSI) as proxies for vegetation growth and water availability, respectively. The trend analysis results showed that changes in NDVI and PDSI were asynchronous over the past three decades. Moreover, we analyzed the spatiotemporal patterns of the correlation coefficient between NDVI and PDSI. The results indicated that the Rvw was getting closer in more areas over the period, but there were differences across ecosystems. Specifically, most croplands and grasslands were primarily constrained by water deficit, which was getting stronger; however, most forests were primarily constrained by water surplus, which was getting weaker. Furthermore, our random forest regression models indicated that the dominant driver of changes in the NDVI-PDSI correlation was atmospheric carbon dioxide (CO2) in more than 45% of grid cells. In addition, the partial correlation analysis results demonstrated that elevated CO2 concentrations not only boosted vegetation growth through the fertilizer effect but also indirectly enhanced water availability by improving water use efficiency (WUE). Overall, this study highlights the important role of atmospheric CO2 in mediating the Rvw under climate change, implying a potential link between vegetation greening and drought risk.
作者机构：
[Wu, Tieniu; Zhang, Yutong] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Wu, TN ] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
关键词：
Water temperature;Soil aggregates;Soil erodibility;Parent materials;Subtropical hilly area
摘要：
Water temperature has an important effect on soil aggregate stability. In this study, six soils derived from different parent materials in the hilly region of southern China were selected, and the mean weight diameter (MWD), geometric mean diameter (GMD), and soil erodibility (K value) were measured under different water temperature conditions. The aim of this study was to investigate the influence of water temperature on soil aggregate stability and erodibility. As the water temperature increased from 5 degrees C to 40 degrees C, the average content of >5 mm water-stable aggregates decreased by 57.13 %, while the average content of <0.25 mm water-stable aggregates increased by 214.41 %. The MWD and GMD of the six different parent soil types exhibited a decreasing trend with increasing water temperature. The trend of the K value was opposite to that of these values. The influence of water temperature on soil aggregate stability is mainly attributed to the thermal effect on the viscosity of soil water and the expansion of clay minerals. As the water temperature increases, the water viscosity coefficient, water density and water surface tension gradually decrease. Moreover, the response of soil aggregate stability and erosion resistance to water temperature varies with soil depth and parent material type. The topsoil exhibits greater sensitivity to water temperature than does the subsoil. Shale (SH) soils and quartz sandstone (QS) soils exhibited higher sensitivities, and Quaternary red clay (QRC) soils exhibited the lowest sensitivity to water temperature among the six soils. This difference is mainly attributed to differences in the contents of expansive clay minerals and organic matter. These results indicate that soil aggregate stability and erosion resistance decrease with increasing water temperature, which may be one reason for severe soil erosion under extremely high temperature and rainfall conditions in the southern red soil hilly region during summer.
