XXII ISPRS Congress 2012: Technical Commission VII

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Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/5: METHODS FOR CHANGE DETECTION AND PROCESS MODELLING]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: UPDATING BUILDING MAPS BASED ON OBJECT EXTRACTION AND BUILDING HEIGHT ESTIMATION L. Zhu, H. Shimamura, K. Tachibana

Document type:: Multivolume work

Structure type:: Chapter

action is 1entioned ing map, the other ns where g map. ts on the they are > objects. to fill the first and forms an 1gs, trees :d by the oving the ects in a order to he DTM face that ; the real 'gmented directly, e objects eas. ite small. e will be nnecting mply be , a local action in 1ethod is > NDSM d, which 1::2/:2D f the 2D centrated the same 1, and so the grids nding to n peaks. he center. ostly go ne roofs. d roofs, a pair of detected the two peaks of the 2D histogram within a watershed region. The ones with grids greater than a certain value are regarded as a building. 2.1.3 Building extraction using MCWS method Since some small buildings with very small areas, low heights and plane roofs are easily misdetected, the MCWS method, which is an improved method based on general watershed segmentation, is applied. Watershed segmentation to gray level images is suitable to separate different objects from each others. But it will not give the actual boundaries of each object. The boundary between two objects by watershed segmentation just locates somewhere between them, not exactly the object contour. Watershed segmentation to gradient image can solve this problem and give a real contour of the object. If we apply watershed segmentation to a gradient image, the catchment basins will be the dark regions of the gradient image, which should theoretically correspond to the homogeneous grey level regions. The watershed segmentation will stop at the contours of the dark objects in the gray level image. However, in practice, this transform produces an important over-segmentation due to noise or local irregularities in the gradient image. To avoid the over-segmentation, a marker controlled watershed is introduced (Gao et al., 2001, Salembier et al., 1994). Here, the watershed segmentation is implemented to the gradient of NDSM (GNDSM). A marker is an area which is the initial of a catchment basin. By giving each object and the background a marker, and making them the catchment bases, the desired objects can be segmented from the background. Buildings, trees, and other off-terrain objects are taken as the foreground objects and are assigned the foreground markers. A foreground marker is a spot. If it is the catchment basin for the gradient then the marker will grow to an object. There will be as many objects as foreground markers. The foreground marker is detected by local maxima. The local maximum of an object may be a spot with certain area as a marker. For the buildings with flat roofs, all the pixels in the roofs will be detected as the local maximums in the ideal case. In practice, most pixels of the roof, especially in the center, will be detected as the marker spot. For some objects, because they have more than one obstruction in the roof, there will be several markers detected and consequently they will be segmented as several objects. This disadvantage can be avoided by merging the large regions with the foreground markers. The ground of NDSM is taken as the background and is assigned the background marker. Because the watershed of the segmentation of the NDSM generally locates between objects, it is initially taken as the marker of the background. Sometimes the background marker crosses large regions so that these objects will grow to the background. A refined procedure is implemented to maintain these foreground markers. 2.1.4 Extraction of newly-built buildings The final result of building object extraction can be acquired by merging the results derived by the MCWS method with that of the LSNAT method. Then, newly-built buildings can be detected by overlying the results of extracted buildings on International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia building map. Newly-built buildings can be detected as extracted building objects where there is no building in the building map. 2.2 Detection of demolished and reconstructed buildings Height information is one of the most important characteristics of the objects on the ground, and shows the status of ground surface. It is also very effective information in order to handle building change, and should be utilized for building change detection. In this study, detection of demolished and reconstructed buildings is performed based on estimating the height of each building using existing building maps and newly- acquired DSMs. Figure 2 shows the illustration of building height estimation. The proposed approach is explained in a step wise procedure below. Inner polygonal buffer > Building height le Outskirt buffer Figure 2. Illustration of building height estimation 2.2.1 Estimation of local ground altitude The first step for building height estimation is to acquire the local ground altitude surrounding each building. Based on the building map data, an outskirt buffer around a building polygon is generated. Then, the minimum height inside the outskirt buffer is explored to acquire the altitude of the local ground area around the building. 2.2.2 Estimation of building altitude The altitude of each building also needs to be acquired. Considering the uncertainty involving the gap between a building polygon and DSM, and the quality of DSM data at the border of a building, etc., an inner polygonal buffer is created inside the building polygon. Then, the altitude of inner polygonal buffer is acquired by exploring the minimum height of the inner polygonal buffer. This altitude corresponds to the altitude of the building polygon. 2.2.3 Building height estimation Next, the height of the building can be estimated directly by subtracting the altitude of the building polygon from the ground altitude surrounding the building. 2.2.4 Extraction of demolished and reconstructed buildings Finally, by comparing the building height with a pre-defined threshold, the status of the building, i.e. unchanged, demolished or reconstructed can be detected. If a building is demolished or reconstructed, the obtained building height should be very low hence can be simply detected.

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