XXII ISPRS Congress 2012: Technical Commission VIII

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

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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:: 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/8: Land]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: IMPROVEMENT OF THERMAL ESTIMATION AT LAND COVER BOUNDARY BY USING QUANTILE Tsukasa Hosomura

Document type:: Multivolume work

Structure type:: Chapter

IMPROVEMENT OF THERMAL ESTIMATION AT LAND COVER BOUNDARY BY USING QUANTILE Tsukasa Hosomura Division of Information System Design, School of Science and Engineering, Tokyo Denki University, Hatoyama, Hiki, Saitama, 350-0394, Japan hosomura@mail.dendai.ac.ip Commission VIil/8 KEY WORDS: Statistics, High Resolution, Classification, Infrared, Accuracy Analysis, Urban, Data Analysis ABSTRACT: Land cover classification was conducted for Landsat ETM image of Urmqi. Maximum likelihood classification algorism was used for this purpose. Classification classes were urban, water body, forest, soil, bare groundl, bare ground2, vegetationl, vegetation2 and vegetation3. Mask image of each land cover was created from the obtained classification image. Thermal band image of each land cover was extracted by using the mask image. In general, mean value and standard deviation are calculated for the thermal band image. However, these values were affected by the difference of ground resolution. In this study, we introduced quantiles to avoid this problem. Quantiles are points taken at regular intervals from the cumulative distribution function. Quantiles showed the effectiveness of decreasing the error caused from the difference of ground resolution. 1. INTRODUCTION The air temperature at the city center is higher than that of the surrounding non-urban areas so that it looks like an island. This phenomenon is so called “Urban Heat Island”. In early days, it has attracted attentions as an environmental problem unique to urban area. The investigation area of Urmqi, which is the regional capital of Xinjiang Uyghr Autonomous Region in the dry northwestern part of China, has gained rapid development in recent decades. Together With economic development, the landscape has changed significantly. Land use/cover change has significant impacts on regional environment. Land surface temperature is an important indicator for assessment of regional environment especially in big cities such as Urumqi where urban heat island can usually be relatively obvious. In this study we aim at specifying the urban expansion characteristics of Urmqi City using Landsat ETM images to detect and evaluate the land use and land cover change and analyze the relationship between land use and heat environment of Urmgqi city. Land cover classification was conducted for Landsat ETM image of Urmgi. Thermal band image of each land cover was extracted by using the mask image. In general, mean value and standard deviation are used for statistic analysis. However, difference of ground resolution between thermal infrared image and other band image influence these statistic variables. In this study, we introduced quantiles to avoid this problem. 2. CONCEPT OF QUANTILE Quantiles are points taken at regular intervals from the cumulative distribution function. Quantiles showed the effectiveness of decreasing the error caused from the difference of ground resolution. The median is the central value of the distribution, such that half the points are less than or equal to it and half are larger than or equal to it. The quantiles divide the distribution into four equal parts, called fourths. The second quantile is the median. The interquartile range corresponds to the distance between the first quantile and the third quantile. 3. THERMAL BAND DATA ANALYSIS In order to analyze relationship between land cover and heat

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