Mapping Banana Plantations from Object-oriented Classification of SPOT-5 Imagery

2009 ◽  
Vol 75 (9) ◽  
pp. 1069-1081 ◽  
Author(s):  
Kasper Johansen ◽  
Stuart Phinn ◽  
Christian Witte ◽  
Seonaid Philip ◽  
Lisa Newton
Keyword(s):  
Object Oriented ◽  
Banana Plantations ◽  
Spot 5

Analysis of wavelet packet and statistical textures for object-oriented classification of forest-agriculture ecotones using SPOT 5 imagery

2011 ◽  
Vol 33 (11) ◽  
pp. 3557-3579 ◽  
Author(s):  
Wei Su ◽  
Chao Zhang ◽  
Jianyu Yang ◽  
Honggan Wu ◽  
Lei Deng ◽  
...  
Keyword(s):  
Wavelet Packet ◽  
Object Oriented ◽  
Spot 5

scholarly journals Assessing Riyadh’s Urban Change Utilizing High-Resolution Imagery

Land ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 193
Author(s):  
Ali Alghamdi ◽  
Anthony R. Cummings
Keyword(s):  
Maximum Likelihood ◽  
High Resolution ◽  
Accuracy Assessment ◽  
Middle Eastern ◽  
Object Oriented ◽  
Training Data ◽  
High Resolution Imagery ◽  
Significant Research ◽  
Desert Areas ◽  
Spot 5

The implications of change on local processes have attracted significant research interest in recent times. In urban settings, green spaces and forests have attracted much attention. Here, we present an assessment of change within the predominantly desert Middle Eastern city of Riyadh, an understudied setting. We utilized high-resolution SPOT 5 data and two classification techniques—maximum likelihood classification and object-oriented classification—to study the changes in Riyadh between 2004 and 2014. Imagery classification was completed with training data obtained from the SPOT 5 dataset, and an accuracy assessment was completed through a combination of field surveys and an application developed in ESRI Survey 123 tool. The Survey 123 tool allowed residents of Riyadh to present their views on land cover for the 2004 and 2014 imagery. Our analysis showed that soil or ‘desert’ areas were converted to roads and buildings to accommodate for Riyadh’s rapidly growing population. The object-oriented classifier provided higher overall accuracy than the maximum likelihood classifier (74.71% and 73.79% vs. 92.36% and 90.77% for 2004 and 2014). Our work provides insights into the changes within a desert environment and establishes a foundation for understanding change in this understudied setting.

scholarly journals SEGMENTATION AND CLASSIFICATION OF NEPAL EARTHQUAKE INDUCED LANDSLIDES USING SENTINEL-1 PRODUCT

2016 ◽  
Vol XLI-B7 ◽  
pp. 769-774
Author(s):  
Saket Kunwar
Keyword(s):  
Data Exchange ◽  
Open Data ◽  
Object Oriented ◽  
Ground Truth ◽  
British Geological Survey ◽  
Exchange Program ◽  
Amplitude Data ◽  
Richter Scale ◽  
Data Commons

On April 26, 2015, an earthquake of magnitude 7.8 on the Richter scale occurred, with epicentre at Barpak (28°12'20''N,84°44'19''E), Nepal. Landslides induced due to the earthquake and its aftershock added to the natural disaster claiming more than 9000 lives. Landslides represented as lines that extend from the head scarp to the toe of the deposit were mapped by the staff of the British Geological Survey and is available freely under Open Data Commons Open Database License(ODC-ODbL) license at the Humanitarian Data Exchange Program. This collection of 5578 landslides is used as preliminary ground truth in this study with the aim of producing polygonal delineation of the landslides from the polylines via object oriented segmentation. Texture measures from Sentinel-1a Ground Range Detected (GRD) Amplitude data and eigenvalue-decomposed Single Look Complex (SLC) polarimetry product are stacked for this purpose. This has also enabled the investigation of landslide properties in the H-Alpha plane, while developing a classification mechanism for identifying the occurrence of landslides.

scholarly journals Classification of Actions or Inheritance also for Methods

1987 ◽  
Vol 16 (231) ◽  
Author(s):  
Bent Bruun Kristensen ◽  
Ole Lehrmann Madsen ◽  
Birger Møller-Pedersen ◽  
Kristen Nygaard
Keyword(s):  
General Class ◽  
Object Oriented ◽  
Wide Range ◽  
Language Classes ◽  
Virtual Classes ◽  
Main Thing

<p>The main thing with the sub-class mechanism as found in languages like C++, SIMULA and Smalltalk is its possibility to express <em>specializations</em>. A general class, covering a wide range of objects, may be specialized to cover more specific objects. This is obtained by three properties of sub-classing: An object of a sub-class inherits the attributes of the super-class, virtual procedure/method attributes (of the super-class) may be specialized in the sub-class, and (in SIMULA only) it inherits the actions of the super-class.</p><p>In the languages mentioned above, virtual procedures/methods of a super-class are specialized in sub-classes in a very primitive manner: they are simply <em>re-defined</em> and need not bear any resemblance of the virtual in the super-class. In BETA, a new object-oriented language, classes and methods are unified into one concept, and by an extension of the virtual concept, virtual procedures/methods in sub-classes are defined as <em>specializations of the virtuals</em> in the super-class. The virtual procedures/methods of the sub-classes thus inherit the attributes (e.g. parameters) and actions from the ''super-procedure/method''.</p><p>In the languages mentioned above only procedures/methods may be virtual. As classes and procedures/methods are unified in BETA this gives also <em>virtual classes</em>. The paper demonstrates, how this may be used to parameterize types and enforce constraints on types.</p>

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