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23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)

作者： Loberternos, R. A. Porpetcho, W. P. Graciosa, J. C. A. Violanda, R. R. Diola, A. G. Dy, D. T. Otadoy, R. E. S. Univ San Carlos Fr Josef Baumgartner Learning Resource Ctr USC Phil LiDAR Res Ctr Talamban Campus Cebu 6000 Philippines Univ San Carlos Dept Phys Theoret & Computat Sci & Engn Grp Cebu 6000 Philippines Univ San Carlos Dept Biol Cebu 6000 Philippines

Traditional remote sensing approach for mapping aquaculture ponds typically involves the use of aerial photography and high resolution images. The current study demonstrates the use of object-based image processing and analyses of LiDAR-data-generated derivative images with 1-meter resolution, namely: CHM (canopy height model) layer, DSM (digital surface model) layer, DTM (digital terrain model) layer, Hillshade layer, Intensity layer, NumRet (number of returns) layer, and Slope layer. A Canny edge detection algorithm was also performed on the Hillshade layer in order to create a new image (Canny layer) with more defined edges. These derivative images were then used as input layers to perform a multi-resolution segmentation algorithm best fit to delineate the aquaculture ponds. In order to extract the aquaculture pond feature, three major classes were identified for classification, including land, vegetation and water. Classification was first performed by using assign class algorithm to classify Flat Surfaces to segments with mean Slope values of 10 or lower. Out of these Flat Surfaces, assign class algorithm was then performed to determine Water feature by using a threshold value of 63.5. The segments identified as Water were then merged together to form larger bodies of water which comprises the aquaculture ponds. The present study shows that LiDAR data coupled with object-based classification can be an effective approach for mapping coastal aquaculture ponds. The workflow currently presented can be used as a model to map other areas in the Philippines where aquaculture ponds exist.

关键词： Object-Based Image Analysis (OBIA) multiresolution segmentation coastal land use fishpond

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OPERATIONAL LAKE MAPPING ON THE SOUTHERN TIBET USING SENTINEL-1 DATA 39

OPERATIONAL LAKE MAPPING ON THE SOUTHERN TIBET USING SENTINE...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Cao, Han Zhang, Hong Wang, Chao Ye, Qinghua Tang, Yixian Chinese Acad Sci Inst Remote Sensing & Digital Earth Beijing 100094 Peoples R China Univ Chinese Acad Sci Beijing 100094 Peoples R China Chinese Acad Sci Inst Tibetan Plateau Res Beijing 100101 Peoples R China

ISBN: (纸本)9781538691540

The Tibet plateau (TP), as the third pole, plays an important role for indicating the global climate change. This study evaluated the potential of SAR data on lake mapping on the southern TP region which is characterized by various complex water conditions. A robust object-oriented lake extraction approach using Sentinel-1 data is proposed. First, an automatic method of selecting regions that obeying bimodal distribution is used to obtain the optimal threshold to identify lakes. Second, Taguchi design experiments are used to obtain the optimal segmentation parameters of multiresolution segmentation and object-oriented classification is applied to extract the lakes. Finally, a postprocessing approach is applied to remove the false alarms due to shadows with auxiliary DEM data and object-based variance of intensity map. Experiments on the Sentinel-1 image demonstrate that the proposed method produces highly reliable lake extents in southern TP, and is potentially applicable to the lake mapping projects on the whole TP.

关键词： Tibet plateau lake extraction bimodality test Taguchi method multiresolution segmentation

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Object-oriented industrial solid waste identification using HJ satellite imagery: a case study of phosphogypsum

Object-oriented industrial solid waste identification using ...

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Conference on Earth Resources and Environmental Remote Sensing/GIS Applications III

作者： Fu, Zhuo Shen, Wenming Xiao, Rulin Xiong, Wencheng Shi, Yuanli Chen, Baisong Minist Environm Protect China Satellite Environm Ctr Fengdedong Rd Beijing 100094 Peoples R China Chinese Acad Fishery Sci Beijing 100141 Peoples R China

ISBN: (纸本)9780819492784

The increasing volume of industrial solid wastes presents a critical problem for the global environment. In the detection and monitoring of these industrial solid wastes, the traditional field methods are generally expensive and time consuming. With the advantages of quick observations taken at a large area, remote sensing provides an effective means for detecting and monitoring the industrial solid wastes in a large scale. In this paper, we employ an object-oriented method for detecting the industrial solid waste from HJ satellite imagery. We select phosphogypsum which is a typical industrial solid waste as our target. Our study area is located in Fuquan in Guizhou province of China. The object-oriented method we adopted consists of the following steps: 1) multiresolution segmentation method is adopted to segment the remote sensing images for obtaining the object-based images. 2) Build the feature knowledge set of the object types. 3) Detect the industrial solid wastes based on the object-oriented decision tree rule set. We analyze the heterogeneity in features of different objects. According to the feature heterogeneity, an object-oriented decision tree rule set is then built for aiding the identification of industrial solid waste. Then, based on this decision tree rule set, the industrial solid waste can be identified automatically from remote sensing images. Finally, the identified results are validated using ground survey data. Experiments and results indicate that the object-oriented method provides an effective method for detecting industrial solid wastes.

关键词： Object-oriented method industrial solid waste identification HJ satellite imagery phosphogypsum Fuquan multiresolution segmentation feature knowledge

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Spatial and Temporal Dynamics of Rangeland Ecosystem Services Across the Shazand Watershed, Iran

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Rangeland Ecology and Management 2023年第1期90卷 45-55页

作者： Mirchooli, Fahimeh Dabiri, Zahra Strobl, Josef Khaledi Darvishan, Abdulvahed Sadeghi, Seyed Hamidreza Department of Watershed Management Engineering Faculty of Natural Resources Tarbiat Modares University presently Lab Expert Sari Agricultural Sciences and Natural Resources University Sari Iran Noor Iran Department of Geoinformatics-Z_GIS University of Salzburg Salzburg Austria Department of Watershed Management Engineering Faculty of Natural Resources Tarbiat Modares University Noor Iran

Human interventions and global environmental changes are increasing and threaten ecosystem services (ES) worldwide. Managing ES is a challenging task;it is essential to understand the temporal and spatial distribution of ES and the benefits derived by a human. However, ES variability in time and space has yet to be studied. Therefore, the current study investigates spatiotemporal variations of different ES indicators, individually and in combination, in the Shazand Watershed across three time periods: 1998, 2008, and 2016. Five indicators were selected to assess different dimensions of ES, including plant production, water provision, soil stability, maintenance of habitats and genetic diversity for plant and animal nurseries and reproduction, and recreation potential. We then used multiresolution segmentation to create a spatial composite indicator measuring the integration of the study indicators. SCI was used to describe spatiotemporal variations of ES through time at the subwatershed level. The results indicated that individual ES indicators display spatial variations across space and time. Moreover, comparing the spatial composite indicator across periods showed that all 24 subwatersheds could not supply more ES. However, the areas located in the central and the western part of the watershed appeared to have better ES conditions. According to the results, revising the current management plans and allocating environmental funding would benefit these areas. The results are applicable for future spatial planning of sustainable ecological conservation strategies for the Shazand Watershed and similar regions. © 2023 The Society for Range Management

关键词： Integrated ecosystem services multiresolution segmentation Spatial dynamic Watershed management Watershed sustainability

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Automatic urban feature extraction using rule-based object-oriented classification: a case study of parts of Pune city, Maharashtra, India

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APPLIED GEOMATICS 2023年第4期15卷 871-884页

作者： Dhorde, Anargha Deshpande, Gauri Datkhile, Pallavi Savitribai Phule Pune Univ Nowrosjee Wadia Coll Res Ctr Pune 1 Maharashtra India Savitribai Phule Pune Univ Nowrosjee Wadia Coll Postgrad Dept Geog Pune 1 Maharashtra India Symbiosis Int Deemed Univ SIU Symbiosis Inst Geoinformat SIG Pune Maharashtra India Indrones Solut Pvt Ltd Navi Mumbai Maharashtra India

Urban areas are gaining attention globally with the implementation of the United Nations sustainable development agenda 2030 where more emphasis is given on making cities inclusive, resilient, safe, and sustainable. Hence, it is crucial to have precise data of urban built-up areas such as the shape, size, and spatial context. It is a challenging task to extract urban built-up features due to continuous modifications in land as well as heterogeneity in spatial and spectral extent of the urban surfaces. The present research attempts to extract urban built up structures using rule-based object-oriented classification. SEaTH, a tool used for feature analysis in eCognition software was applied to select the discrete features and optimum thresholds that allow more and more separability during classification. With respect to diversity in urban areas, two urban patches of Pune city were selected where one patch is the core part of the city with a congested network of roads and buildings and another patch is located in the outskirts comprises of modern multi-story buildings and relatively broad roads. multiresolution segmentation with scale parameter of 5 with a shape 0.1 and compactness of 0.5 was finally accepted after a lot of trial iterations for both the areas. Using the SEaTH tool, some of the best object features such as shape properties, spectral bands, and indices (NDVI) were selected for the assessment of the separability and threshold. A rule-based classification was performed to acquire land use/land cover with an overall accuracy of 92% for the city core and 91% for the suburb. The k-hat value obtained was 0.81 and 0.88 for the city core and suburb area, respectively. With incorporating shape parameters in image classification, the SEaTH method applied hierarchically the shape features such as density, compactness, and shape index as the best features to separate the buildings and roads. The NDVI spectral index demonstrated in this study proved beneficial to cla

关键词： Object-oriented classification NDVI multiresolution segmentation SEaTH

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Urban Tree Canopy Detection Using Object-Based Image Analysis for Very High Resolution Satellite Images : A Literature Review

Urban Tree Canopy Detection Using Object-Based Image Analysi...

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International Conference on Technologies for Sustainable Development (ICTSD 2015)

作者： Yadav, Sarika Rizvi, Imdad Kadam, Shailaja Univ Mumbai Terna Engn Coll Navi Mumbai 400706 India

ISBN: (纸本)9781479981878

Urban Tree Canopy (UTC) is the layer of leaves, branches and stems of trees that cover the ground when viewed from above. Remotely sensed data have played an important role in detecting urban morphologies effectively. Remote sensing datasets contain more information of earth surface as compared with usual urban maps hence used in urban planning and management. Very high resolution (VHR) satellite imageries provide resolution less than 1m. These imageries have enhanced the applications of remote sensing. Timely and accurate information of urban land cover and biophysical parameters is crucial. Earth observations which are being useable play an important role in detecting, management and solving environmental problems such as climate changes, deforestation, disasters, land use, water resource and carbon cycle. With the help of high resolution satellite imageries it is possible to get the details on earth surface. A different approach is used to get the efficient result called Object-based image analysis (OBIA) in which the image is divided into homogeneous regions prior to classification instead of classifying individual pixels. These are called segments, or image objects. OBIA have gain popularity as a method bridging the gap between the increasing amount of detailed geospatial data and the inefficient results of conventional pixel base classifiers.

关键词： OBIA VHR images Remote sensing Urban vegetation multiresolution segmentation

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A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE ANALYSIS 23

A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE A...

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23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)

作者： Kavzoglu, T. Erdemir, M. Yildiz Tonbul, H. Gebze Tech Univ Geomat Engn Dept TR-41400 Gebze Turkey

Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

关键词： Object Based Image Analysis Region-based scale Classification multiresolution segmentation Estimation of Scale Parameter (ESP)

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Automatic detection and agronomic characterization of olive groves using high-resolution imagery and LIDAR data 16

Automatic detection and agronomic characterization of olive ...

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Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI was part of the International Symposium on Remote Sensing

作者： Caruso, T. Ruehl, J. Sciortino, R. Marra, F. P. La Scalia, G. Univ Palermo Dipartimento Sci Agr & Forestali Fac Agr Via Sci Ed 4 I-90128 Palermo Italy Univ Palermo Dipartimento Ingn Civile Ambientale Aerospaziale I-90128 Palermo Italy Univ Palermo Dipartimento Ingn Chim Informat Gestionale I-90128 Palermo Italy

ISBN: (纸本)9781628413021

The Common Agricultural Policy of the European Union grants subsidies for olive production. Areas of intensified olive farming will be of major importance for the increasing demand for oil production of the next decades, and countries with a high ratio of intensively and super-intensively managed olive groves will be more competitive than others, since they are able to reduce production costs. It can be estimated that about 25-40% of the Sicilian oliviculture must be defined as "marginal". Modern olive cultivation systems, which permit the mechanization of pruning and harvest operations, are limited. Agronomists, landscape planners, policy decision-makers and other professionals have a growing need for accurate and cost-effective information on land use in general and agronomic parameters in the particular. The availability of high spatial resolution imagery has enabled researchers to propose analysis tools on agricultural parcel and tree level. In our study, we test the performance of WorldView-2 imagery relative to the detection of olive groves and the delineation of olive tree crowns, using an object-oriented approach of image classification in combined use with LIDAR data. We selected two sites, which differ in their environmental conditions and in their agronomic parameters of olive grove cultivation. The main advantage of the proposed methodology is the low necessary quantity of data input and its automatibility. However, it should be applied in other study areas to test if the good results of accuracy assessment can be confirmed. Data extracted by the proposed methodology can be used as input data for decision-making support systems for olive grove management.

关键词： multiresolution segmentation Nearest Neighbour classification tree crown detection NDVI World View-2 LIDAR

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Image segmentation for the purpose of object-based classification

Image segmentation for the purpose of object-based classific...

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23rd International Geoscience and Remote Sensing Symposium (IGARSS 2003)

作者： Darwish, A Leukert, K Reinhardt, W Univ Bundeswehr Munich GIS Lab D-85577 Neubiberg Germany

The main aim of this research is to find optimum segmentation parameters for extracting different land cover classes. A relatively new segmentation approach, multiresolution segmentation, is being examined using two d... 详细信息

ISBN: (纸本)0780379292

关键词： multiresolution segmentation object-based classification land-cover classification

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segmentation of CT images using the watershed transformation on graphs with a-priori tissue models

Segmentation of CT images using the watershed transformation...

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Medical Imaging 1999 Conference - Image Processing

作者： Wegner, S Hütter, R Oswald, H Fleck, E Humboldt Univ Fac Med German Heart Inst Berlin & Charite D-13353 Berlin Germany

ISBN: (纸本)0819431338

The combination of the watershed transformation on graphs with a tissue classification is presented. The watershed transformation on graphs results in hierarchical segmentation volumes that differ in region number and size. If an anatomical object corresponds to a region in a segmentation volume it has to be selected, since the region would be merged with the most similar neighbor region in the following volume. Such an object selection can be done using object descriptions. A possible approach is presented in this paper.

关键词： watershed transformation on graphs multiresolution segmentation classification

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