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Large-scale spatial variability in loess landforms and their evolution, Luohe River Basin, Chinese Loess Plateau

GEOMORPHOLOGY 2022年 415卷

作者： Wei, Hong Xiong, Liyang Zhao, Fei Tang, Guoan Lane, Stuart N. Nanjing Normal Univ School of Geog Nanjing 210023 Peoples R China Nanjing Normal Univ Key Lab Virtual Geog Environm Minist Educ Nanjing 210023 Peoples R China Jiangsu Ctr Collaborat Innovat Geog Informat Resou Nanjing 210023 Peoples R China Univ Lausanne Inst Earth Surface Dynam IDYST CH-1015 Lausanne Switzerland

Loess landform variability across large spatial extents needs to be analyzed to understand the formation and evolution of loess landscapes. This is becoming increasingly possible via the automated analysis of remotely-sensed data. Here, we quantify loess landforms using an object-based image analysis (OBIA) method and use this classification to describe the spatial variability of loess landforms. Quantitative indicators are used to drive the spatial variability analysis of loess landforms and explain their spatio-temporal evolution. Moreover, the hypsometric integral (HI) and topographic interpolation are employed to investigate soil erosion and develop-ment patterns of loess landscape. Results show that the OBIA method classified loess landforms to an accuracy of 88.7 %. The derived metrics in terms of the area, slope and complexity of landform shape allow the determi-nation of the spatial structure of the loess landscapes. The HI value of the entire basin is 0.486, representing the mature stage of landform development, with relatively severe surface erosion. Correlation analysis of HI values and related indicators in the sub-basins shows that HI is poorly correlated with the area proportion of loess landform types and the total erosion volume in the basin but shows a relatively strong correlation with the volume of erosion per unit area.

关键词： Loess landform variability Hypsometric integral object-based image analysis Landscape pattern indices Chinese Loess Plateau

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Exploring agricultural landscape change from the second half of the twentieth century onwards: combining aerial imagery with farmer perspectives

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LANDSCAPE ECOLOGY 2024年第7期39卷 120-120页

作者： Mohr, Franziska Pazur, Robert Debonne, Niels Dossche, Rebekka Helfenstein, Julian Hepner, Samuel Levers, Christian Verburg, Peter H. Buergi, Matthias Swiss Fed Res Inst WSL Zurcherstr 111 CH-8903 Birmensdorf Switzerland Univ Bern Inst Geog Bern Switzerland Slovak Acad Sci Inst Geog Bratislava Slovakia Vrije Univ Amsterdam Inst Environm Studies IVM Environm Geog Grp Amsterdam Netherlands Univ Genoa Dept Antiqu Philosophy Hist DAFIST Genoa Italy Wageningen Univ Soil Geog & Landscape Grp Wageningen Netherlands Agroscope Agroecol & Environm Zurich Switzerland Fed Res Inst Rural Areas Forestry & Fisheries Thunen Inst Biodivers Johann Heinrich Thunen Inst Braunschweig Germany

Context Anthropogenic landscape change is an important driver shaping our environment. Historical landscape analysis contributes to the monitoring and understanding of these change processes. Such analyses are often focused on specific spatial scales and single research methods, thus covering only limited aspects of landscape *** Here, we aim to assess the potential of combining the analysis of historical aerial imagery and local stakeholder interviews for landscape change studies using a standardized mapping and interviewing *** We compared six agricultural landscapes across Europe and mapped land-cover using historical aerial imagery (starting between 1930 and 1980, depending on data availability, until recent years) with an object-based image analysis and random forest classification. For local perspectives of landscape change, we conducted oral history interviews (OHIs) with (almost) retired farmers. Comparing recorded landscape changes from both approaches provided insight into advantages of combining these two *** object-based analysis enabled the identification of high-resolution land-cover dynamics, with scale enlargement and cropland/grassland expansion being the most commonly recurring trends across European landscapes. Perceived landscape changes identified in the OHIs included changes in farm management, landscape structure, and infrastructure. Farmers also reported drivers and personal values associated with landscape change. Combining the two historical landscape analysis tools resulted in a qualitative and quantitative understanding of changes in land-cover, land use, and land *** Comparing physical land-cover change with local farmer perspectives is key to a comprehensive understanding of landscape change. There are different ways the two methods can be combined, leading to different venues for science and policy making.

关键词： Agricultural landscape Landscape history Land-use change Mixed-method approach object-based image analysis Oral history

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Rainfall-induced landslide inventories for Lower Mekong based on Planet imagery and a semi-automatic mapping method

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GEOSCIENCE DATA JOURNAL 2022年第2期9卷 315-327页

作者： Amatya, Pukar Kirschbaum, Dalia Stanley, Thomas Univ Space Res Assoc Columbia MD USA Goddard Earth Sci Technol & Res Columbia MD USA NASA Hydrol Sci Lab Goddard Space Flight Ctr Greenbelt MD USA

Fatal landslides occur every year during the rainy season (June-November) in the Lower Mekong Region (LMR). There is an urgent need to develop a landslide early warning system in the LMR. In collaboration with the Asian Disasters Preparedness Center and NASA's SERVIR Programme, we are regionalizing the global Landslide Hazard Assessment System for Situational Awareness model for the LMR (LHASA-Mekong). A robust set of landslide inventories are needed to effectively train the machine learning-based LHASA-Mekong model. In this study, the Semi-Automatic Landslide Detection (SALaD) system was modified by incorporating a change detection module (SALaD-CD) to produce rainfall event-based landslide inventories using pre- and post-imagery from RapidEye and PlanetScope for various locations in the LMR that were identified based on media and government reports. These rainfall-induced landslides are published as initiation points for ease of use. In total, we created 22 inventories: 2 in Laos, 4 in Myanmar, 1 in Thailand and 15 in Vietnam. These inventories are being used to train the LHASA-Mekong model and quantify the effects of Land use/Land cover change on landslide susceptibility. These open data will be a valuable resource for advancing landslide studies in this region.

关键词： landslides Lower Mekong Region object-based image analysis SALaD SALaD-CD SERVIR-Mekong

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Sentinel-2 mapping of a turbid intertidal seagrass meadow in Southern Vietnam

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GEOCARTO INTERNATIONAL 2023年第1期38卷 Article: 2186490页

作者： Trinh, Xuan Truong Nguyen, Lam Dao Takeuchi, Wataru Univ Tokyo Inst Ind Sci Tokyo Japan Vietnam Natl Space Ctr Ho Chi Minh City Space Technol Applicat Ctr Ho Chi Minh City Vietnam

Seagrass ecosystems are crucial to the carbon cycle, biodiversity, fisheries, and erosion prevention. However, there are gaps in mapping seagrass in tropical coastal waters due to turbidity and constantly changing tidal dynamics. To tackle such issues, tidal heights and reflectance of 33 Sentinel-2 images were used to calculate a multitemporal composite of Sentinel-2 images, which was classified using the Random Forest classifier. UAV images classified with object-based image analysis provided ground truth for training and validation. The effectiveness of water column correction and using the multitemporal composite was evaluated by comparing overall classification accuracy. As a result, applying water column correction improved classification accuracy from 80.4% to 80.6%, while using the multi-temporal composite improved accuracy to 88.6%, among the highest accuracy achieved for seagrass classification in turbid waters. The combined protocol could lead to advances in quantifying seagrass distribution in the tropical coastal waters and their carbon sequestration capacity, resolving significant uncertainties in blue carbon estimation.

关键词： blue carbon ecosystems seagrass mapping time series analysis object-based image analysis tidal dynamics unmanned aerial vehicles

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A semi-automated approach for quantitative mapping of woody cover from historical time series aerial photography and satellite imagery

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ECOLOGICAL INFORMATICS 2020年 55卷 101012-101012页

作者： Whiteside, Timothy G. Esparon, Andrew J. Bartolo, Renee E. Environm Res Inst Supervising Scientist Darwin NT Australia

Savanna landscapes are characterised by a canopy of discontinuous tree cover overlying an understorey of shrubs and continuous grass cover. The distribution of trees (woody cover) is variable both spatially and temporally. analysis of woody cover dynamics can provide a spatial and temporal envelope encompassing variability is useful for informing mine closure criteria. With the impending closure of Ranger uranium mine, ecologically appropriate closure criteria for ecosystem restoration are being developed through a framework of rehabilitation standards. One such closure criteria is canopy cover and historical woody cover is being used to derive the range in woody cover that can be expected over time once the mine site has been revegetated. This study reports on the development and testing of a technique for extracted woody cover from remotely sensed data (in the form of historical aerial photography and satellite imagery) in the areas adjacent to Ranger uranium mine in the World Heritage listed Kakadu National Park, northern Australia. An object-based image analysis technique was applied to four data sets from four different dates: greyscale, true colour and colour infrared aerial photo mosaics (from 1964, 1976 and 1981 respectively) and a high spatial resolution satellite image (from 2010). Overall accuracies of woody cover from each of the data sets exceeded 94%. In addition, proportional cover derived from this method displays linear relationships to cover derived from visual estimates. Due to the success of the technique, it will be applied to more data sets from different dates over the study area to assess the variability of woody cover over time to inform ecosystem restoration criteria for the mine closure.

关键词： object-based image analysis Savanna woody cover dynamics Kakadu National Park Time-series

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Automated detection of migrating Gray whales and measurement of their bearing in satellite imagery

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MARINE MAMMAL SCIENCE 2024年第0期

作者： Rodofili, Esteban Nicolas Houegnigan, Ludwig Lecours, Vincent Klarenberg, Geraldine Cuesta, Eduardo Univ Florida Sch Nat Resources & Environm Gainesville FL USA Univ Florida Sch Forest Fisheries & Geomat Sci Gainesville FL USA Univ Politecn Cataluna Signal Theory & Commun Dept Barcelona Spain Univ Politecn Cataluna Intelligent Data Sci & Artificial Intelligence Res Barcelona Spain Univ Quebec Chicoutimi Lab Expertise & Rech Geog Appl Chicoutimi PQ Canada

Satellite images could aid in studying baleen whale migration routes given their extensive spatial coverage. We developed two object-based image analysis (OBIA) workflows to automatically detect migrating whales and their orientation. We used three sections of a Worldview-3 satellite image off California with migrating gray whales (Eschrichtius robustus), alternating training and testing under a three-fold approach in eCognition, with three classes: whale, water, and confounding objects (e.g., sea foam). After a workflow with 202 classification features, we applied feature selection through a minimum redundancy maximum relevance algorithm and retained 15 features. This selection was used in a second workflow which yielded fewer false negatives (FNs) and especially, fewer false positives (FPs) (22.6% vs. 11.1% FNs rate, 7599.6% vs. 1352.6% FP over detectable rate). While FPs were still considerable, image grid cells to review were reduced to less than 3% of cells for full manual analysis. Using Moore's test for paired circular data, we failed to find significant differences between manual and both automated or semiautomated orientation measurements (corrected for whales measured from head to tail). Most whales were oriented in the southeastern quadrant. The results are promising for satellite image studies of migration routes.

关键词： baleen whales migration routes object-based image analysis remote-sensing

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A Knowledge-based procedure for remote sensing image classification

A Knowledge-based procedure for remote sensing image classif...

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The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

作者： Limin Zhang Tao Xu Yingfu Yu Jianting Zhang Department of Scientific Research Naval Aeronautical and Astronautical University Yantai China Institute of Information Fusion Naval Aeronautical and Astronautical University Yantai China

ISBN: (纸本)9781479951499

object-based image analysis(OBIA)in combination with domain knowledge is an important methodology for remote sensing image *** can deal with semantic gap *** this paper,a knowledge-based procedure for remote sensing image classification is *** knowledge is represented with semantic network,which guides the initial classification of the image.A quantitative matching degree is used in the modification of the initial *** proposed procedure is much more efficient compared with method in literature.

关键词： object-based image analysis semantic network remote sensing image classification matching degree

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INTEGRATION OF SAR AND GEOBIA FOR THE analysis OF TIME-SERIES DATA

INTEGRATION OF SAR AND GEOBIA FOR THE ANALYSIS OF TIME-SERIE...

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IEEE International Geoscience and Remote Sensing Symposium

作者： D. Amitrano F. Cecinati G. Di Martino A. Iodice P. -P. Mathieu D. Riccio G. Ruello University of Napoli Federico II Napoli Italy University of Bath Bath UK European Space Agency ESA ESRIN Frascati Italy

In this work, we present a new architecture for the analysis multitemporal SAR data combining classic synthetic aperture radar processing and geographical object-based image analysis. The architecture exploits the characteristics of the recently introduced RGB products of the Level-1α and Level-1β families, employing self-organizing map clustering and object-based image analysis aiming at the definition of opportune layers measuring scattering and geometric properties of candidate objects to classify. The obtained results have been compared with those given by literature and turned out to provide high degree of accuracy and negligible false alarms. The discussion is supported by an example concerning small reservoir mapping in semi-arid environment.

关键词： Multitemporal synthetic aperture radar Classification Self-organizing map clustering object-based image analysis

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object based BUILDING EXTRACTION AND BUILDING PERIOD ESTIMATION FROM UNMANNED AERIAL VEHICLE DATA

OBJECT BASED BUILDING EXTRACTION AND BUILDING PERIOD ESTIMAT...

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The ISPRS Technical Commission III Midterm Symposium on "Developments, Technologies and Applications in Remote Sensing"

作者： R.Comert O.Kaplan Department of Geomatics Engineering Faculty of Engineering and Natural SciencesGumushane University Earth and Space Sciences Institute Anadolu University

The aim of this study is to examine whether it is possible to estimate the building periods with respect to the building heights in the urban scale seismic performance assessment studies by using the building height retrieved from the unmanned aerial vehicle(UAV) data. For this purpose, a small area, which includes eight residential reinforced concrete buildings, was selected in Eskisehir(Turkey) city center. In this paper, the possibilities of obtaining the building heights that are used in the estimation of building periods from UAV based data, have been investigated. The investigations were carried out in 3 stages;(i) Building boundary extraction with object based image analysis(OBIA),(ii) height calculation for buildings of interest from n DSM and accuracy assessment with the terrestrial survey.(iii) Estimation of building period using height information. The average difference between the periods estimated according to the heights obtained from field measurements and from the UAV data is 2.86% and the maximum difference is 13.2%. Results of this study have shown that the building heights retrieved from the UAV data can be used in the building period estimation in the urban scale vulnerability assessments.

关键词： Building Period Building Height UAV object-based image analysis

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SUPERPIXEL-based SEGMENTATION OF REMOTE SENSING imageS THROUGH CORRELATION CLUSTERING

SUPERPIXEL-BASED SEGMENTATION OF REMOTE SENSING IMAGES THROU...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Giuseppe Masi Raffaele Gaetano Giovanni Poggi Giuseppe Scarpa DIETI University Federico II of Naples

ISBN: (纸本)9781479979301

In this paper a new object-oriented segmentation method for high-resolution remote sensing images is proposed. To limit computational complexity, a preliminary superpixel representation of the image is obtained by means of a suitable water-shed transform. Then, a region adjacency graph is associated with the superpixels, with edge weights accounting for region similarity/dissimilarity. The final segmentation is then obtained by means of a graph-cutting approach, following a correlation clustering formulation. The optimal cut can be obtained by solving a Integer Linear Programming (ILP) problem, whose complexity, however, grows rapidly with the image size. Much faster near-optimal solutions are obtained, here, with a greedy solution. Experiments on a real-world high-resolution remote sensing image prove the potential of the approach.

关键词： object-based image analysis Superpixel segmentation Graph partitioning Correlation clustering Integer linear programming Integer linear programming images region adjacency graph high resolution remote sensing model-based image analysis remote sensing image SIZE Cluster analysis THROUGH

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