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SSRN 2022年

作者： Jiang, Zhimeng Wu, Hao Lin, Anqi Hu, Qiong Zhu, Wenchao College of Urban and Environmental Sciences Central China Normal University Wuhan430079 China Hubei Province Key Laboratory for Geographical Process Analysis and Simulation Wuhan430079 China

Spatial patterns are essential for examining the sustainability derived from land systems. Constructing spatial patterns for sustainable land development is now high on the global agenda to guarantee human welfare. However, there is as yet no consensus on the technical framework for optimizing the spatial pattern of land development (SPLD) contrapose a prominent grain-producing area (PGPA). To narrow this gap, we propose a synthetic framework to shape a more reasonable SPLD for a sustainable development strategy by measuring the equilibrium between the production–living–ecological space (PLES) functions and the resource and environment carrying capacity (RECC). Taking a prominent grain-producing area (PGPA) as the object, a case study involving the Jianghan Plain (JHP) in China is conducted, leading to the following novel insights. (i) The quality of PLES and RECC in a PGPA is affected by multiple dimensions: agriculture, ecology, environment, and society. The indices of the PLES function and the RECC have significant spatial heterogeneity. SPLD in regions with fragile ecological environments and strong development is often under overload pressure. (ii) Based on the spatial zoning results of SPLD, the five partitions were taken as the optimized objects, including zones of the eco-economic, model-agricultural, core-living, eco-conservation, and coordinated-development. The land function definition of these five types of zoning covers the production-living-ecological function orientation in a PGPA. (iii) The SPLD optimization framework proposed above has strong universality because it comprehensively considers the multi-dimensional spatial functional needs of PGPA. In this study, an optimization decision framework of SPLD based on measurement and zoning was established for a PGPA. Significantly, the introduced framework is applicable and practical for optimizing SPLD from a sustainable equilibrium perspective, and the findings have considerable implications for sustai

关键词： Sustainable development

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Measuring and understanding changes in the physical built environment of cities with street view images

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Urban Informatics 2025年第1期4卷 1-23页

作者： Zhou, Yang Thill, Jean-Claude Liu, Xingjian Zhong, Chen Tu, Wei Key Laboratory for Geographical Process Analysis and Simulation of Hubei Province College of Urban and Environmental Sciences Central China Normal University Wuhan China Department of Geography and Earth Sciences University of North Carolina at Charlotte Charlotte USA Department of Urban Planning and Design University of Hong Kong Hong Kong SAR China The Bartlett Centre for Advanced Spatial Analysis (CASA) University College London London UK Key Laboratory for Geo-Environmental Monitoring of Great Bay Area School of Architecture and Urban Planning Shenzhen University Shenzhen China Guangdong Key Laboratory for Urban Informatics Shenzhen University Shenzhen China State Key Laboratory of Subtropical Building and Urban Science Shenzhen China

Street view images (SVIs) may provide information on near-surface urban changes which are not necessarily captured by spaceborne remote sensing data. The application of SVIs in assessing diverse built environment changes at the street level and over time remains challenging. This paper presents a stepwise rule-based method to identify key types of urban built environment changes using multi-year SVIs. In particular, physical/built environment changes along streets are evaluated based on proposed Street Units of analysis (SUA) that account for both street layouts and street view features. The approach employs sharp variations of visual attributes derived from deep learning segmentation model DeepLabv3+. A stepwise rule-based algorithm classifies SUAs. Using panoramic SVIs from 2015–2019 in Wuhan, China, we identify critical types of changes such as those related to highway bridges, sidewalk increases, building increases, road losses, greenness increases, and mixed changes. Identified changes take place on over 50% of roads in the study area. In addition, the robustness of proposed approach is assessed based on results produced by manual labeling and by a fuzzy rough sets analysis. The approach is found to be robust and effective by having an 81.7% agreement with manually labeled analysis and an 80.5% agreement with fuzzy rough sets analysis. Overall, this study contributes to the development of a cost effective and efficient method for detecting physical changes on SUAs, which can be further utilized in studies that link urban changes, space use, and policy interventions.

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Spatiotemporal-Statistical-Modelling-Based Soil Loss Equation Calibration (Ssmbslec) by Air-Ground Collaboration

SSRN

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SSRN 2024年

作者： Li, Chang Yao, Jiayin Ding, Yijia Wu, Yijin Wu, JunZao Wu, Man Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province College of Urban and Environmental Science Central China Normal University Wuhan China Faculty of Resources and Environmental Science Hubei University Wuhan China Water and Soil Conservation Monitoring Station in Caidian District Wuhan China Water and soil conservation and planned water conservation station in Caidian District Wuhan China

The soil erosion module (SEM) calculated by the soil loss equation (SLE) is currently a computer simulation value, which may not be consistent with the actual value of field soil erosion. Therefore, it is necessary to calibrate the SEM to make it more approximate to the actual value. Additionally, due to the existence of spatiotemporal non-stationarity, traditional ordinary least squares (OLS) may not calibrate the deviation between the simulation value and actual value well. To address the aforementioned issues, this paper proposes the first spatiotemporal-statistical-modelling-based calibration method for a soil loss equation (SSMBSLEC) through air-ground collaboration. This method utilises data from unmanned aerial vehicles (UAVs) and ground monitoring stations to quantitatively calibrate the SEM. The experimental results from the Caidian District area demonstrate the effectiveness of this approach. The statistical calibration models were ranked in order of accuracy, from high to low, as follows: The study employed four regression techniques: geographically weighted regression, geographically and temporally weighted regression, temporally weighted regression, and OLS. The results of the hotspot analysis, based on space-time cubes, showed that the spatial law consistency between the actual value of soil erosion and SEM was the strongest, followed by the spatiotemporal law consistency, and the time consistency. These findings suggest that the accuracy of each SSMBSLEC model is affected by these factors. This study could enhance the methods and theory of water and soil conservation, promote interdisciplinary collaboration between it and spatial information science, and provide a research basis for the quantitative estimation of the actual value of SEM. © 2024, The Authors. All rights reserved.

关键词： Erosion

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Soil erosion assessment by RUSLE with improved P factor and its validation:Case study on mountainous and hilly areas of hubei Province,China

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International Soil and Water Conservation Research 2021年第3期9卷 433-444页

作者： Pei Tian Zhanliang Zhu Qimeng Yue Yi He Zhaoyi Zhang Fanghua Hao Wenzhao Guo Lin Chen Muxing Liu Key Laboratory for Geographical Process Analysis&Simulation of Hubei Province Central China Normal UniversityWuhan430079PR China School of Geosciences The University of EdinburghEH89XPUK Department of Geography University of MontrealH2V 0B3MontrealQCCanada State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Institute of Water and Soil ConservationNorthwest A&F UniversityYangling712100Shaanxi PR China

The Revised Universal Soil Loss Equation(RUSLE)is widely used to estimate regional soil ***,quantitative impacts of soil and water conservation(SWC)measures on conservation practice factor(P)of the RUSLE remain largely unclear,especially for the mountainous and hilly *** this study,we improved the RUSLE by considering quantitative impacts of different SWC measures on the P factor *** improved RUSLE was validated against the long-term(2000-2015)soil erosion monitoring data obtained from 96 runoff plots(15—35°)in mountainous and hilly areas of hubei Province,China;the result presented a high accuracy with the determination coefficient of *** on the erosion monitoring data of 2018 and 2019,the Root Mean Square Error of the result by the improved RUSLE was 28.0%smaller than that by the original RUSLE with decrement of 19.6%—24.0%in the average P factor values,indicating that the soil erosion modelling accuracy was significantly enhanced by the improved *** low P factor values appeared for farmlands with tillage measures(P<0.53),grasslands with engineering measures(P<0.23),woodlands with biological measures(P<0.28),and other land use types with biological measures(P<0.51).The soil erosion modulus showed a downward trend with the corresponding values of 1681.21,1673.14,1594.70,1482.40 and 1437.50 t km^(-2)a-1 in 2000,2005,2010,2015 and 2019,*** applicability of the improved RUSLE was verified by the measurements in typical mountainous and hilly areas of hubei Province,China,and arrangements of SWC measures of this area were proposed.

关键词： Conservation practice factor(P) Soil and water conservation measure Soil erosion Land use Monitoring data

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From statistics to grids:A two-level model to simulate crop pattern dynamics

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Journal of Integrative Agriculture 2022年第6期21卷 1786-1798页

作者： XIA Tian WU Wen-bin ZHOU Qing-bo Peter HVERBURG YANG Peng HU Qiong YE Li-ming ZHU Xiao-juan Key Laboratory for Geographical Process Analysis&Simulation Hubei Province/College of Urban&Environmental ScienceCentral China Normal UniversityWuhan 430079P.R.China Key Laboratory of Agricultural Remote Sensing Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081P.R.China Agricultural Information Institute Chinese Academy of Agricultural SciencesBeijing 100081P.R.China Institute for Environmental Studies VU University AmsterdamAmsterdam 1085The Netherlands Department of Geology Ghent UniversityGhent 9000Belgium Commercial and Economic Law School China University of Political Science and LawBeijing 100088P.R.China

Crop planting patterns are an important component of agricultural land *** patterns have been significantly changed due to the combined impacts of climatic changes and socioeconomic ***,the extent of these changes and their possible impacts on the environment,terrestrial landscapes and rural livelihoods are largely unknown due to the lack of spatially explicit datasets including crop planting *** fill this gap,this study proposes a new method for spatializing statistical data to generate multitemporal crop planting pattern *** method features a two-level model that combines a land-use simulation and a crop pattern *** output of the first level is the spatial distribution of the cropland,which is then used as the input for the second level,which allocates crop censuses to individual gridded cells according to certain *** method was tested using data from 2000 to 2019 from Heilongjiang Province,China,and was validated using remote sensing *** results show that this method has high accuracy for crop area *** crop pattern datasets over a given time period can be important supplementary information for remote sensing and thus support a wide range of application in agricultural land systems.

关键词： crop planting pattern spatialization simulation spatiotemporal change remote sensing

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Improved modeling and analysis of the patch size–frequency distribution of forest disturbances in China based on a Landsat forest cover change product

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International Journal of Digital Earth 2021年第2期14卷 181-201页

作者： Dan-Xia Song Chengquan Huang Tao He Joseph O.Sexton Ainong Li Sike Li Hao Wu John R.Townshend College of Urban and Environmental Sciences Central China Normal UniversityWuhanPeople’s Republic of China Hubei Provincial Key Laboratory for Geographical Process Analysis and Simulation Central China Normal UniversityWuhanPeople’s Republic of China Department of Geographical Sciences University of MarylandCollege ParkMDUSA School of Remote Sensing and Information Engineering Wuhan UniversityWuhanPeople’s Republic of China terraPulse IncGaithersburgMDUSA Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengduPeople’s Republic of China School of Earth Atmosphere and EnvironmentMonash University–Clayton CampusVictoriaAustralia

Forest disturbances have been altering the ecological properties of ecosystems;meanwhile,disturbance events of varying sizes create different structures and functions for a forest ***,size and frequency are important attributes of disturbances,and their relationship should be *** present a hierarchical method through the modeling of the overall trend of the size–frequency distribution and the characterization of the non-constant variances of disturbance sizes at each frequency *** method was demonstrated to accurately model the sizes as well as the corresponding frequencies;thus,the total disturbed area and number of disturbance patches were both accurately *** applying the method to 13 provinces in China,consistent patterns were revealed by the modeling results and remote-sensing-based product,showing that between 2000 and 2005,forests in most provinces were dominated by moderate disturbances(10 ha1000 ha)occurred in the northeastern and northwestern *** study concludes that the proposed method can improve the representation of the size–frequency distribution of forest disturbances.

关键词： Forest disturbance patch size remote sensing forestry

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UDHF2-Net: Uncertainty-diffusion-model-based High-Frequency TransFormer Network for Remotely Sensed Imagery Interpretation

arXiv

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arXiv 2024年

作者： Zhang, Pengfei Li, Chang Zhang, Yongjun Qin, Rongjun Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province College of Urban and Environmental Science Central China Normal University Wuhan China School of Remote Sensing and Information Engineering Wuhan University China Department of Civil Environmental and Geodetic Engineering Department of Electrical and Computer Engineering Translational Data Analytics Institute The Ohio State University ColumbusOH United States

Remotely sensed imagery interpretation (RSII), including semantic segmentation and change detection, faces the three major problems: (1) objective representation of spatial distribution patterns with coexistence of spatial stationary and non-stationary;(2) edge uncertainty problem caused by downsampling encoder and intrinsic edge noises (e.g., mixed pixel and edge occlusion etc.);and (3) false detection problem caused by geometric registration error in change detection. To solve the aforementioned problems, uncertainty-diffusion-model-based high-Frequency TransFormer network (UDHF2-Net) is the first to be proposed, whose superiorities are as follows: (1) a spatially-stationary-and-non-stationary high-frequency connection paradigm (SHCP) is proposed to enhance the interaction of spatially frequency-wise stationary and non-stationary features to yield high-fidelity edge extraction result. Inspired by HRFormer, SHCP proposes high-frequency-wise stream to replace high-resolution-wise stream in HRFormer through the whole encoder-decoder process with parallel frequency-wise high-to-low streams, so it improves the edge extraction accuracy by continuously remaining high-frequency information;(2) a mask-and-geo-knowledge-based uncertainty diffusion module (MUDM), which is a self-supervised learning strategy, is proposed to improve the edge accuracy of extraction and change detection by gradually removing the simulated spectrum noises based on geo-knowledge and the generated diffused spectrum noises;(3) a frequency-wise semi-pseudo-Siamese UDHF2-Net is the first to be proposed to balance accuracy and complexity for change detection. Besides the aforementioned spectrum noises in semantic segmentation, MUDM is also a self-supervised learning strategy to effectively reduce the edge false change detection from the generated imagery with geometric registration error. In semantic segmentation experiments, UDHF2-Net achieved the best mIoU values of 92.00%, 87.31% and 55.27% respecti

关键词： Semantic Segmentation

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A prototype web-based analysis platform for drought monitoring and early warning

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International Journal of Digital Earth 2020年第7期13卷 817-831页

作者： Mattijn van Hoek Jie Zhou Li Jia Jing Lu Chaolei Zheng Guangcheng Hu Massimo Menenti State Key Laboratory of Remote Sensing Science Chinese Academy of SciencesInstitute of Remote Sensing and Digital EarthBeijingPeople’s Republic of China HKV Consultants LelystadThe Netherlands Key Laboratory for Geographical Process Analysis&Simulation of Hubei Province/College of Urban and Environmental SciencesCentral China Normal UniversityWuhanPeople’s Republic of China

It has long been recognized that an effective drought monitoring and early warning system,which provides functions for real-time condition monitoring and prediction,risk assessment,information dissemination and response recommendation,is very important for the preparedness for and mitigation of drought *** this article,we review the currently existing drought monitor and early warning systems,discuss applicable remote sensing datasets and drought indicators and present the development of a web-based quasi-real-time Global Drought Monitoring&analysis Platform(Web-GDMAP).The Web-GDMAP is built upon a series of indicators derived from multi-source satellite remote sensing data and various other sources of *** a technical perspective,the Web-GDMAP system includes a series of components from data storage,model implementation and distribution,to client-side visualization and user intuitive *** a theoretical perspective,the Web-GDMAP system integrates multi-indicators on different aspects of drought,including anomalies in precipitation,anomalies in land surface thermal and vegetation conditions,water deficit of soil and plants,*** case studies on applying the developed Web-GDMAP in the Asian region are *** improvements and perspectives are discussed.

关键词： Drought monitoring remote sensing web-based Open Geospatial Consortium(OGC) time series

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High nitrogen fertilizer input enhanced the microbial network complexity in the paddy soil

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Soil Ecology Letters 2024年第2期6卷 97-109页

作者： Yanan Chen Yan Li Tianyi Qiu Haoran He Ji Liu Chengjiao Duan Yongxing Cui Min Huang Chunyan Wu Linchuan Fang The Research Center of Soil and Water Conservation and Ecological Environment Chinese Academy of Sciences and Ministry of EducationYangling712100China State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Institute of Soil and Water Conservation CAS and MWRYangling712100China University of Chinese Academy of Sciences Beijing100049China Institute of Environment Resource and Soil Fertilizer Zhejiang Academy of Agricultural SciencesHangzhou310021China College of Natural Resources and Environment Northwest A&F UniversityYangling712100China Hubei Province Key Laboratory for Geographical Process Analysis and Simulation Central China Normal UniversityWuhan430079China Department of Ecohydrology Leibniz Institute of Freshwater Ecology and Inland FisheriesBerlin12587Germany Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking UniversityBeijing100871China College of Resources and Environmental Engineering Wuhan University of TechnologyWuhan430070China CAS Center for Excellence in Quaternary Science and Global Change Xi’an710061China

N fertilizer altered bacterial community compositions by changing soil nutrients.•Bacterial ammonia oxidation became predominated with the increasing N rate.•Excessive N input caused the information of a more complex microbial network.•Intensified microbial competition by excessive N was due to negative link ***(N)fertilization drives the structure and function of soil microbial communities,which are crucial for regulating soil biogeochemical cycling and maintaining ecosystem *** the N fertilizer effects on soil microbial composition and diversity have been widely investigated,it is generally overlooked that ecosystem processes are carried out via complex associations among microbiome ***,we examined the effects of five N fertilization levels(0,135,180,225,and 360 kg N ha−1)on microbial co-occurrence networks and key functional taxa such as ammonia-oxidizers in paddy *** results showed that N addition altered microbial community composition,which were positively related to soil total N and available phosphorus(P)*** abundance of ammonia-oxidizing archaea(AOA)significantly decreased after N addition,whereas ammonia-oxidizing bacteria(AOB)increased in N360 *** with low-N group(N0 and N135),the high-N group(N225 and N360)shaped more complex microbial webs and thus improved the stability of the microbial *** least squares path modeling further revealed that N fertilizer had a higher effect on microbial network complexity in the high-N group(0.83)than the low-N group(0.49).Although there were more positive links across all microbial networks,the proportion of negative links significantly increased in the high-N network,suggesting that excess N addition aggravated the competition among microbial *** these interactions between microbial communities and N fertilization advances our understanding of biogeochemical processes in paddy soils and their effects on nutrient supply to

关键词： nitrogen fertilizer paddy soil co-occurrence network microbial interaction

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Early Detection of Invasive Phragmites Australis at the Tidal Marsh-Forest Ecotone with Airborne Lidar

SSRN

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SSRN 2024年

作者： Xiong, Biao Han, Siyuan Messerschmidt, Tyler C. Kirwan, Matthew L. Gedan, Keryn Qi, Man School of Computer Science and Artificial Intelligence Wuhan University of Technology 122 Luoshi Rd Wuhan430070 China Virginia Institute of Marine Science William & Mary Gloucester PointVA United States Department of Biological Sciences The George Washington University WashingtonDC United States Key Laboratory of Geographical Process Analysis and Simulation of Hubei Province College of Urban and Environmental Sciences Central China Normal University Wuhan430079 China

Wetlands across North America are invaded by an introduced lineage of the common reed Phragmites australis, and sea level rise has exacerbated the spread of this species. P. australis at tidal marsh-forest ecotones has rapidly been expanding into deteriorating forest, colonizing understory environments ahead of native marsh species. Early detection of P. australis at the ecotone will be critical to the management of this invasive species in coming decades. In this study, we develop and validate a new method for early detection of P. australis, using open access airborne LiDAR data that can uniquely penetrate the tree canopy and detect P. australis within the forest understory. The method was designed for areas of sparse to moderate tree cover, such as the forest edge where trees are dying and P. australis is expanding, where understory species mapping was previously impossible with most spectral data. To differentiate P. australis from shrubs and other understory herbaceous plants, we tested the effectiveness of several LiDAR-derived spatial metrics, including Mean distance, Point density, Scatter, Omnivariance, and Eigentropy, as inputs to a Support Vector Machine (SVM) classifier, followed by a smoothing algorithm to avoid occasional obstacles or disturbances. We compare among metrics and single- vs. multiple- metric-based classifications. The resulting best early detection method of P. australis achieved a classification accuracy of 91.48% at the development site, and between 56.16% and 80.65% accuracy at other test sites. This algorithm provides a cost-effective and high accuracy method of detecting understory P. australis using public airborne LiDAR data. Larger-scale application of this method will provide coastal resource managers and policy-makers with distribution maps of P. australis through time in open environments and the forest understory. More generally, this approach provides a framework for mapping understory species and plant functional groups usin

关键词： Wetlands

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