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/8: Land]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: CLOUD DETECTION BASED ON DECISION TREE OVER TIBETAN PLATEAU WITH MODIS DATA Lina Xu, Shenghui Fang, Ruiging Niu, Jiong Li

Document type:: Multivolume work

Structure type:: Chapter

CLOUD DETECTION BASED ON DECISION TREE OVER TIBETAN PLATEAU WITH MODIS DATA Lina Xu*® * Shenghui Fang*, Ruiging Niu ^ Jiong Li? 2 School of Remote Sensing and Information Engineering , Wuhan University, Wuhan 430079,China, silvaxu@sina.com ? China University of Geosciences, Wuhan 430074, China Commission VIII, WG VIII/10 KEY WORDS: cloud detection, MODIS, Tibetan Plateau, snow cover, decision tree ABSTRACT: Snow cover area is a very critical parameter for hydrologic cycle of the Earth. Furthermore, it will be a key factor for the effect of the climate change. An unbelievable situation in mapping snow cover is the existence of clouds. Clouds can easily be found in any image from satellite, because clouds are bright and white in the visible wavelengths. But it is not the case when there is snow or ice in the background. It is similar spectral appearance of snow and clouds. Many cloud decision methods are built on decision trees. The decision trees were designed based on empirical studies and simulations. In this paper a classification trees were used to build the decision tree. And then with a great deal repeating scenes coming from the same area the cloud pixel can be replaced by “its” real surface types, such as snow pixel or vegetation or water. The effect of the cloud can be distinguished in the short wave infrared. The results show that most cloud coverage being removed. A validation was carried out for all subsequent steps. It led to the removal of all remaining cloud cover. The results show that the decision tree method performed satisfied. 1. INTRODUCTION In high altitude regions one of the important water sources are snow. So snow cover is very important in high mountainous areas where snow pack can often remain through the summer months and snow melt provides runoff and water supply for the downstream population. Many areas of the world have large gaps between observation locations or have no observation stations at all. Satellites have enabled researchers to obtain snow information on a global scale and monitor its effects on global climate (Rango, 1996). The Tibetan Plateau is a unique geomorphic unit and is called “the third pole” of the Earth by its highest altitude. So it is the most sensitive area in the world to hydrological cycle and climatic change. Mapping the snow cover area of the Tibetan Plateau is very important for the regional climatic change and Hydrological cycle. Considering that the Earth’s surface is normally covered by a great amount of cloud at any time (Partridge and Platt 1976), for reliable results from the retrieval of surface characteristics using remotely sensed data absolutely cloud-free pixels are required. But it is unrealistic. We have to consider about how to detect clouds and to remove them. Clouds have a very similar reflectance as snow. So it is very difficult to distinguish clouds from snow. There are many challenges in mapping snow cover because of the existence of cloud, but three items would be the most inconvenient truth (1) the snow cover are marked by the high reflectance of the cloud; (2) the snow cover are disturbed by the radiance of the cloud; (3) the clouds are misestimate to be snow. The Moderate Resolution Imaging Spectroradiometer (MODIS) is a 36-band spectroradiometer measuring visible and infrared radiation and obtaining data that are being used to derive * silvaxu@sina.com; phone +86-27-67883251; fax +86-27-67883251 products ranging from vegetation, land surface cover, and ocean chlorophyll fluorescence to cloud and aerosol properties, fire occurrence, snow cover on the land, and sea ice cover on the oceans. The first MODIS instrument was launched on board the Terra satellite in December 1999, and the second was launched on Aqua in May 2002. MODIS provides snow cover information at 500m spatial and daily temporal resolutions. The MODIS snow product is part of the MODIS snow and sea ice global mapping project conducted by NASA’s Cryospheric Sciences Branch at the Goddard Space Flight Center. NASA creates daily snow maps indicating snow covered land, land without snow cover, cloud cover, seawater, lake water, and lake ice (Ault, 2006). There are often multiple views of snow cover in each day under clear skies. In winter MODIS snow cover products had high accuracy, but decreasing accuracy for the rest of the seasons, especially in winter-spring or fall-winter season. The main factor is the existence of the cloud in the snow mapping. So for the snow mapping the biggest challenge is to detect cloud and move it. In this paper, a decision tree was built to recognize the clouds from background for the MODIS data over Tibetan Plateau. And then cloud pixels were replaced by snow or vegetation or other pixels with a great deal repeating scenes coming from the same area. The goal of this study was to remove the cloud covered pixels from the snow cover data completely and to produce continuous maps of snow coverage over the Tibetan Plateau.

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