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Kategorie szczegółowe BISAC

Spatial Statistics: Geospatial Information Modeling and Thematic Mapping

ISBN-13: 9780367865627 / Angielski / Miękka / 2020 / 184 str.

Mohammed A. Kalkhan
Spatial Statistics: Geospatial Information Modeling and Thematic Mapping Mohammed A. Kalkhan 9780367865627 CRC Press - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Spatial Statistics: Geospatial Information Modeling and Thematic Mapping

ISBN-13: 9780367865627 / Angielski / Miękka / 2020 / 184 str.

Mohammed A. Kalkhan
cena 230,14
(netto: 219,18 VAT:  5%)

Najniższa cena z 30 dni: 216,55
Termin realizacji zamówienia:
ok. 22 dni roboczych.

Darmowa dostawa!
inne wydania

Geospatial information modeling and mapping have become important tools for the investigation and management of natural resources at the landscape scale. This book reviews the types and applications of geospatial information data, such as remote sensing, GIS, and GPS, as well as their integration into landscape-scale geospatial statistical model

Kategorie:
Nauka, Matematyka
Kategorie BISAC:
Mathematics > Prawdopodobieństwo i statystyka
Technology & Engineering > Remote Sensing & Geographic Information Systems
Technology & Engineering > Environmental - General
Wydawca:
CRC Press
Język:
Angielski
ISBN-13:
9780367865627
Rok wydania:
2020
Ilość stron:
184
Oprawa:
Miękka
Wolumenów:
01

"[This book] covers many topics that are poorly treated by others. ... Chapter 2 on sampling is a true gem. It covers all the standard approaches, but in addition has an extensive discussion of multiphase or double sampling which Kalkhan has used extensively in his own research. There is also an extensive discussion of a case study in which a pixel nested plot (PNP) sampling design is used. This is useful material for researchers and course instructors alike. ... This reviewer enjoyed Chapter 4 immensely. It provides a stimulating discussion of geospatial analysis and modeling including the topics of variogram fitting and kriging. These are pitched at just the right level for most applied researchers who want to use these approaches as a tool to solve their spatial analysis problems. A particular treat is the explanation of spatial autoregressive approaches, binary classification trees and the GARP genetic algorithm. These are topics invariably neglected in many of the standard texts."
—Nigel Waters, Geomatica, Vol. 65, No. 4, 2011

Geospatial Information Technology. Data Sampling Methods and Applications. Spatial Pattern and Correlation Statistics. Geospatial Analysis and Modeling–Mapping. R Statistical Package. Working with Geospatial Information Data. Index.

Dr. Mohammed A. Kalkhan has over 20 years experience in research and teaching at Colorado State University in Fort Collins, Colorado. As a member of the Natural Resource Ecology Laboratory (NREL) there, he has also served as an affiliate faculty in the Department of Forest, Rangeland, and Watershed Stewardship, and as an advisor for the Interdisciplinary Graduate Certificate in Geospatial Science, Graduate Degree Program in Ecology (GDPE), The School of Global Environmental Sustainability (SOGES), and Department of Earth Resources (currently the Department of Geosciences) at Colorado State University (CSU).





Dr. Kalkhan received his BSc in Forestry (1973) and MSc in Forest Mensuration (1980) from the College of Agriculture and Forestry, the University of Mosul, Iraq. He received his PhD in forest biometrics- remote sensing applications from the Department of Forest Sciences at Colorado State University, USA, in 1994. From 1975 to 1982, he was a lecturer in the Department of Forestry, College of Agriculture and Forestry, University of Mosul. In 1994, he joined the Natural Resource Ecology Laboratory.





Dr. Kalkhan’s main interests are in the integration of field data, remote sensing, and GIS with geospatial statistics to understand landscape parameters through the use of a complex model with thematic mapping approaches, including sampling methods and designs, biometrics, determination of uncertainty and mapping accuracy assessment.



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