Evaluation of data fusion and image segmentation in earth observation based rapid mapping workflows

Witharana, Chandi; Civco, Daniel L.; Meyer, Thomas H.

doi:10.1016/j.isprsjprs.2013.10.005

Cited by 44 publications

(22 citation statements)

References 34 publications

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“…Additionally, this pushed the development of a classification approach that is less dependent on spectral information and more focused on context. Witharana et al [37] evaluated the impacts of data fusion, such as pan-sharpening.…”

Section: Discussionmentioning

confidence: 99%

Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco

et al. 2014

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This study aims at the detection of gully-affected areas by applying object-based image analysis in the region of Taroudannt, Morocco, which is highly affected by gully erosion while simultaneously representing a major region of agro-industry with a high demand of arable land. As high-resolution optical satellite data are readily available from various sensors and with a much better temporal resolution than 3D terrain data, an area-wide mapping approach to extract gully-affected areas using only optical satellite imagery was developed. The methodology additionally incorporates expert knowledge and freely-available vector data in a cyclic object-based image analysis approach. This connects the two fields of geomorphology and remote sensing. The classification results show the successful implementation of the developed approach and allow conclusions on the current distribution of gullies. The results of the classification were checked against manually delineated reference data incorporating expert knowledge based on several field campaigns in the area, resulting in an overall classification accuracy of 62%. The error of omission accounts for 38% and the error of commission for 16%, respectively. Additionally, a manual assessment was carried out to assess the quality of the applied classification algorithm. The limited error of omission contributes with 23% to the overall error of omission and the limited error of commission contributes with 98% to the overall error of commission. This assessment improves the results and confirms the high quality of the developed approach for area-wide mapping of gully-affected areas in larger regions. In the field of landform Remote Sens. 2014, 6 8288 mapping, the overall quality of the classification results is often assessed with more than one method to incorporate all aspects adequately.

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Section: Discussionmentioning

confidence: 99%

Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco

et al. 2014

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“…GEOBIA starts by segmenting the image grouping pixels into objects, then uses a wide range of object properties to classify the objects or extract object properties from the image [33,36,37]. Multiresolution segmentation is a popular method of segmentation in the remote-sensing field [36].…”

Section: Segmentationmentioning

confidence: 99%

Watershed Land Cover/Land Use Mapping Using Remote Sensing and Data Mining in Gorganrood, Iran

Minaei

Kainz

2016

IJGI

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Abstract:The Gorganrood watershed (GW) is experiencing considerable environmental change in the form of natural hazards and erosion, as well as deforestation, cultivation and development activities. As a result of this, different types of Land Cover/Land Use (LCLU) change are taking place on an intensive level in the area. This research study investigates the LCLU conditions upstream of this watershed for the years 1972, 1986, 2000 and 2014, using Landsat MSS, TM, ETM+ and OLI/TIRS images. LCLU maps for 1972, 1986, and 2000 were produced using pixel-based classification methods. For the 2014 LCLU map, Geographic Object-Based Image Analysis (GEOBIA) in combination with the data-mining capabilities of Gini and J48 machine-learning algorithms were used. The accuracy of the maps was assessed using overall accuracy, quantity disagreement and allocation disagreement indexes. The overall accuracy ranged from 89% to 95%, quantity disagreement from 2.1% to 6.6%, and allocation disagreement from 2.1% for 2014 to 2.7% for 2000. The results of this study indicate that a significant amount of change has occurred in the region, and that this has as a consequence affected ecosystem services and human activity. This knowledge of the LCLU status in the area will help managers and decision makers to develop plans and programs aimed at effectively managing the watershed into the future.

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“…Multiresolution segmentation, an algorithm used for segmenting HSR imagery, has been used widely and has achieved good accuracy [20]. It is a bottom-up region-merging technique from pixel level into image object (IO) polygon level using three parameters: scale, shape, and compactness [20,31,32]. We set algorithm parameters to obtain the best polygons for each of the objects in the imagery by inserting parameters previously used for real-color composite of RGB color composite orthophotos on the pixel level: 10 on scale, 0.5 shape, and 0.9 compactness, into the software.…”

Section: Study Area and Datamentioning

confidence: 99%

Pitch and Flat Roof Factors’ Association with Spatiotemporal Patterns of Dengue Disease Analysed Using Pan-Sharpened Worldview 2 Imagery

Rinawan

Tateishi

Raksanagara

et al. 2015

IJGI

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Dengue disease incidence is related with the construction of a house roof, which is an Aedes mosquito habitat. This study was conducted to classify pitch roof (PR) and flat roof (FR) surfaces using pan-sharpened Worldview 2 to identify dengue disease patterns (DDPs) and their association with DDP. A Supervised Minimum Distance classifier was applied to 653 training data from image object segmentations: PR (81 polygons), FR (50), and non-roof (NR) class (522). Ground validation of 272 pixels (52 for PR, 51 for FR, and 169 for NR) was done using a global positioning system (GPS) tool. Getis-Ord score pattern analysis was applied to 1154 dengue disease incidence with address-approach-based data with weighted temporal value of 28 days within a 1194 m spatial radius. We used ordinary least squares (OLS) and geographically weighted regression (GWR) to assess

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Evaluation of data fusion and image segmentation in earth observation based rapid mapping workflows

Cited by 44 publications

References 34 publications

Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco

Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco

Watershed Land Cover/Land Use Mapping Using Remote Sensing and Data Mining in Gorganrood, Iran

Pitch and Flat Roof Factors’ Association with Spatiotemporal Patterns of Dengue Disease Analysed Using Pan-Sharpened Worldview 2 Imagery

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