XXII ISPRS Congress 2012: Technical Commission VIII

Shortis, M.; Shimoda, H.; Cho, K.

Bibliographic data

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:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Year of publication:: 2014

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663822514

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B8)

Language:: English

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

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

Editor:: Shortis, M.; Shimoda, H.; Cho, K.

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:: [VIII/6: Agriculture, Ecosystems and Bio-Diversity]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: ESTIMATION OF VEGETATION HEIGHT THROUGH SATELLITE IMAGE TEXTURE ANALYSIS Z. I. Petrou, C. Tarantino, M. Adamo, P. Blonda, M. Petrou

Document type:: Multivolume work

Structure type:: Chapter

considered absent in our study. Thus, another aim of the paper is to extract surrogate measures of vegetation height extraction through Remote Sensing, in case primary data are not available or affordable. For the extraction of the texture measures, a mul- tispectral Quickbird image of the Italian Natura 2000 protected site of Le Cesine is used. 2 MATERIALS 2.1 Study area The methods discussed in the paper are tested at the Le Cesine site. Le Cesine is a Natura 2000 protected site located on the Adriatic site of the south eastern part of Apulia region, Italy (Fig- ure 1). It covers around 3.48km? and is one of the oldest pro- tected areas in Apulia. The area comprises a complex of coastal lagoons, as well as various canals, marshes and humid grasslands. Helophytic, halophilous and dry therophytic vegetation alternate and create interesting mosaics. Cladium mariscus communities are the most common helophytic vegetation species. The woody vegetation is mainly characterized by Pinus halepensis and Quer- cus ilex, while the scrubby vegetation by Erica forskalii. 2.2 Data The only available data source for height estimation in our study is a very high resolution multispectral image from the Quickbird sensor, acquired in mid July 2005. The image is of 2.4m spatial resolution and contains four bands, lying in the spectral areas of blue (450-520nm), green (520-600nm), red (630-690nm) and near-infrared (760—900nm). For validation purposes, a habitat map of Le Cesine, expressed in the GHC scheme, from the same period is used. GHC, a tree- structure classification system proposed to include all European habitats, is based on life forms. It consists of five main classes, each of which is further split into several subclasses, resulting in a total of 160 habitat categories (Bunce et al, 2008). For certain main classes, e.g. Trees and Shrubs, vegetation height is not only fundamental for the recognition of the habitat class of landscape patches from remote sensors, but, often, the only way, since the spectral reflectance properties of the patches may not be particularly distinctive. An indicative example includes the discrimination between the low and mid phanerophyte class (LPH/MPH), being shorter than 2m, and the tall phanerophytes (TPH), with above 2m height. The discrimination between these (semi-)natural habitats is important, since they have distinct char- acteristics causing or revealing different ecological properties and functions. Figure 1 presents the location of Le Cesine in Italy and the avail- able Quickbird image, where the green band is drawn in gray- scale. The boundaries of the protected area overlay the Quick- bird image. The areas of LPH/MPH habitats, as extracted from the habitat map, are indicated as white dotted patches, the TPH habitats as dark dotted patches, while all the rest habitats remain transparent and let the image intensity appear underneath. 3 METHODS In our study, Quickbird image alone is used to characterize habi- tats based on their height and discriminate between LPH/MPH and TPH categories. Vegetation height is approximated indirectly by quantifying the homogeneity of the ground through the pro- posed texture analysis measures. The high spatial resolution of International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 322 the image allows the extraction of such measures able to cap- ture local variations in the ground structure and provide an ac- curate indication of the homogeneity of the ground. The patches of interest characterized as LPH/MPH and TPH are detected in the Quickbird image, based on the GHC habitat map. For these patches, the proposed texture measures are calculated on a per pixel basis. For each measure, its average value in the pixels of the patch is extracted. For the tall phanerophyte patches these values are expected to be significantly larger than those for the low/mid phanerophyte patches, reflecting their larger heterogene- ity. The texture measures are calculated for all bands of the Quickbird image, in order to examine the discriminatory capa- bility of each band. Local variance, as a measure of energy, local entropy and local binary patterns are employed in the calculated measures. 3.1 Local Variance The first measure we apply to capture local variations in texture is based on local variance. Around each pixel of the selected LPH/MPH or TPH patch, a small neighborhood is considered. The neighborhood is defined as a square window of predefined size around the central pixel. The variance of the pixel intensi- ties in the neighborhood is calculated and assigned to the central pixel. Since the discrimination of habitats is meaningful on a per patch basis, the average value of the variance values of the pixels of the patch is extracted, providing an indication of the intra-patch heterogeneity and, indirectly, a surrogate of the patch vegetation height. The same procedure is applied for all Quickbird bands. 3.2 Local Entropy In order to detect local variations in texture, entropy-based mea- sures can be employed. Entropy, as introduced in information theory by Shannon (1949), offers, in general terms, an indication of randomness in the studied data; in that sense, heterogeneous patches as far as their pixel brightness is regarded, as the ones depicting tall vegetation habitats, are expected to have higher en- tropy values than patches with low vegetation. Similarly to vari- ance, a local measure of entropy is calculated on a per pixel basis. For each pixel c of a selected patch, entropy is calculated in a sur- rounding window, using k H(c)=— }_ p() log (pli). (0) i=l where k is the total number of different pixel intensities, or gray values, present in the window and p(?) the frequency of appear- ance of value i in the window, i.e. the ratio of the number of pix- els with value i in the window to the total number of pixels of the window. An interesting trade-off takes place: on the one hand, the window needs to be rather small in order to increase spatial resolution and capture local variations in the texture. On the other hand, in order to have reliable and meaningful statistical analysis, the number of gray levels has to decrease, through further quan- tization of the pixel values, as the window size decreases. As an example, for a window of dimensions 9 x 9 pixels, the image should be requantized to at most 8 gray levels, so that we have 81 pixels to populate the 8 gray level bins when forming the his- togram of the window under consideration. Two schemes were tested, one with the entire region of interest being requantized to 8 gray levels, and one with each window being requantized indi- vidually. 3.3 Local Entropy Ratio Aiming at capturing local variations of a small neighborhood around each pixel compared with the existing variations in the extent tropy | sizes : extrac windo is assi homo pared are pr incluc in the the pi: Outer that tl ble st: numb than t eight wind create

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