Developing Online Visualization and Analysis Services for NASA Satellite-Derived Global Precipitation Products during the Big Geospatial Data Era

Big Data ◽  
2014 ◽  
pp. 105-130 ◽  
Keyword(s):  
Geospatial Data ◽  
Global Precipitation

Web Based GIS Application using Open Source Software for Sharing Geospatial Data

2015 ◽  
Vol 4 (1) ◽  
pp. 1224-1228 ◽  
Author(s):  
Debasish Chakraborty ◽  
◽  
Debanjan Sarkar ◽  
Shubham Agarwal ◽  
Dibyendu Dutta ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Geospatial Data ◽  
Web Based ◽  
Gis Application

Using the potential of peripheral green areas of cities for educational and recreational purposes on the example of Stary Sącz, Nowy Targ and Kraków

2020 ◽  
Vol 65 (1) ◽  
pp. 53-63
Author(s):  
Mateusz Kulig ◽  
Anna Przeniczny ◽  
Piotr Ogórek
Keyword(s):  
Land Cover ◽  
Environmental Protection ◽  
Public Spaces ◽  
Geospatial Data ◽  
Valuable Resource ◽  
Green Areas

AbstractGreen areas located on the peripheries of cities have the potential to become green public spaces not only of recreational but also educational character, promoting at the same time the knowledge about environmental protection. The cities included in the research belong to the małopolskie voivodeship (Lesser Poland voivodeship). With the use of geospatial data of land cover, as well as territorial forms of environmental protection, it was pointed that 48.4% of forest, wooded and shrub green areas located within city borders are covered by a form of environmental protection, thus being a valuable resource of significant nature potential. Making such spaces available in a conscious and attractive way is presented on the example of projects implemented in the cities of: Stary Sącz, Nowy Targ and Kraków. The presented projects were used to make recommendations for city authorities to create green public spaces.

PERBANDINGAN SEBARAN CURAH HUJAN HASIL OBSERVASI SATELIT GPM DENGAN MODEL CUACA WRF (Studi Kasus: Siklon Tropis Cempaka Dan Dahlia, 27 Nov – 3 Des 2017)

2019 ◽  
Vol 3 ◽  
pp. 1063
Author(s):  
Fatkhuroyan Fatkhuroyan
Keyword(s):  
Weather Research And Forecasting ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Japan Aerospace Exploration Agency ◽  
Weather Research

Satelit GPM (Global Precipitation Measurement) merupakan proyek kerjasama antara NASA (National Aeronautics and Space Administration) dan JAXA (Japan Aerospace Exploration Agency) serta lembaga internasional lainnya untuk membuat satelit generasi terbaru dalam rangka pengamatan curah hujan di bumi sejak 2014. Model Cuaca WRF (Weather Research and Forecasting) merupakan model cuaca numerik yang telah dipakai oleh BMKG (Badan Meteorologi Klimatologi dan Geofisika) untuk pelayan prediksi cuaca harian kepada masyarakat. Pada tanggal 27 November – 3 Desember 2017 telah terjadi bencana alam siklon tropis Cempaka dan Dahlia di samudra Hindia sebelah selatan pulau Jawa. Tujuan Penelitian ialah untuk mengetahui sebaran akumulasi curah hujan antara observasi satelit GPM dan model cuaca WRF, serta keakuratan model WRF terhadap observasi satelit GPM saat terjadinya bencana alam tersebut. Metode yang dipakai ialah dengan melakukan analisa meteorologi pertumbuhan terjadinya siklon tropis tersebut hingga terjadinya hujan sangat lebat secara temporal maupun spasial. Dari hasil analisa disimpulkan bahwa satelit GPM memiliki luasan sebaran curah hujan yang lebih kecil daripada sebaran hujan model cuaca WRF pada saat siklon tropis Cempaka dan Dahlia. Bias akumulasi sebaran hujan model cuaca WRF juga cukup bagus terhadap satelit GPM sehingga dapat dilakukan antisipasi dampak hujan lebat yang terjadi.

Forest canopy disturbance geospatial data for Lake Superior basin, USA, 1985-2008

2014 ◽  
Author(s):  
Ian W. Housman ◽  
Mark D. Nelson ◽  
Charles H. Perry ◽  
Kirk M. Stueve ◽  
Chengquan Huang
Keyword(s):  
Forest Canopy ◽  
Lake Superior ◽  
Geospatial Data ◽  
Canopy Disturbance

Forest canopy disturbance geospatial data for Lake Michigan basin, USA, 1985-2008

2014 ◽  
Author(s):  
Ian W. Housman ◽  
Mark D. Nelson ◽  
Charles H. Perry ◽  
Kirk M. Stueve ◽  
Chengquan Huang
Keyword(s):  
Forest Canopy ◽  
Lake Michigan ◽  
Geospatial Data ◽  
Michigan Basin ◽  
Canopy Disturbance

Robust Watermarking Scheme for GIS Vector Maps

2018 ◽  
Vol 31 (1) ◽  
pp. 277 ◽  
Author(s):  
Methaq Talib Gaata
Keyword(s):  
Main Idea ◽  
Geospatial Data ◽  
Robust Watermarking ◽  
Digital Map ◽  
Statistical Measures ◽  
Data Authentication ◽  
Two Factors ◽  
Illegal Copying ◽  
Value Decomposition ◽  
Watermarking Scheme

  With the fast progress of information technology and the computer networks, it becomes very easy to reproduce and share the geospatial data due to its digital styles. Therefore, the usage of geospatial data suffers from various problems such as data authentication, ownership proffering, and illegal copying ,etc. These problems can represent the big challenge to future uses of the geospatial data. This paper introduces a new watermarking scheme to ensure the copyright protection of the digital vector map. The main idea of proposed scheme is based on transforming  the digital map to frequently domain using the Singular Value Decomposition (SVD) in order to determine suitable areas to insert the watermark data. The digital map is separated into the isolated parts.Watermark data are embedded within the nominated magnitudes in each part when satisfied the definite criteria. The efficiency of proposed watermarking scheme is assessed within statistical measures based on two factors which are fidelity and robustness. Experimental results demonstrate the proposed watermarking scheme representing ideal trade off for disagreement issue between distortion amount and robustness. Also, the proposed scheme shows  robust resistance for many kinds of attacks.

Access and Integration on Geospatial Data and its Distributed Query

2010 ◽  
Vol 12 (4) ◽  
pp. 532-540 ◽  
Author(s):  
Ang GAO ◽  
Rongguo CHEN ◽  
Yanqing ZHAO ◽  
Xun YAN
Keyword(s):  
Geospatial Data ◽  
Distributed Query

Geospatial Data Analytics : A Machine Learning Perspective

2020 ◽  
Author(s):  
Saneev Kumar Das ◽  
Meenakshi Pant
Keyword(s):  
Machine Learning ◽  
Data Analytics ◽  
Geospatial Data

Creation and update of geospatial data of the Russian

2014 ◽  
Vol 885 (3) ◽  
pp. 2-9
Author(s):  
G.G. Pobedinskiy ◽  
Keyword(s):  
Geospatial Data
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