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Voltar para Imagery, Automation, and Applications

Comentários e feedback de alunos de Imagery, Automation, and Applications da instituição Universidade da Califórnia, Davis

4.9
estrelas
501 classificações
92 avaliações

Sobre o curso

Welcome to the last course of the specialization (unless your continuing on to the capstone project, of course!). Using the knowledge you’ve learned about ArcGIS, complete technical tasks such raster calculations and suitability analysis. In this class you will become comfortable with spatial analysis and applications within GIS during four week-long modules: Week 1: You'll learn all about remotely sensed and satellite imagery, and be introduced to the electromagnetic spectrum. At the end of this week, you'll be able to find and download satellite imagery online and use it for two common types of analysis: NDVI and trained classification. Week 2: You'll learn how to use ModelBuilder to create large processing workflows that use parameters, preconditions, variables, and a new set of tools. We'll also explore a few topics that we don't really have time to discuss in detail, but might whet your appetite for future learning in other avenues: geocoding, time-enabled data, spatial statistics, and ArcGIS Pro. Week 3: In week three, we'll make and use digital elevation models using some new, specific tools such as the cut fill tool, hillshades, viewsheds and more. We'll also go through a few common algorithms including a very important one: the suitability analysis. Week 4: We'll begin the final week by talking about a few spatial analyst tools we haven't yet touched on in the specialization: Region Group to make our own zones, Focal Statistics to smooth a hillshade, Reclassify to change values, and Point Density to create a density surface. Finally, we'll wrap up by talking about a few more things that you might want to explore more as you start working on learning about GIS topics on your own. Take Geospatial and Environmental Analysis as a standalone course or as part of the Geographic Information Systems (GIS) Specialization. You should have equivalent experience to completing the first, second, and third courses in this specialization, "Fundamentals of GIS," "GIS Data Formats, Design, and Quality", and "Geospatial and Environmental Analysis," respectively, before taking this course. By completing the fourth class you will gain the skills needed to succeed in the Specialization capstone....

Melhores avaliações

SM

Jul 17, 2017

The course contents are up to date and equip the learner to face the real world of Remote sensing and GIS. I encourage those who still hesitate to get enrolled to make their decision soon.....

EA

Jan 23, 2020

An amazing course! well organized, very informative, and rich with resources and useful materials, with an excellent discussion forum to discuss the course subjects.

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76 — 90 de 90 Avaliações para o Imagery, Automation, and Applications

por Alex V

Dec 02, 2016

outstanding.

por nura u k

Nov 10, 2016

Yes for sure

por Jessica B

Jan 10, 2017

fantastic!

por Atti

Nov 14, 2016

i like it

por Ahmed M A A

Feb 05, 2019

thanks

por Sanaullah K

Nov 01, 2018

Great

por Mahamadou K

May 18, 2020

cool

por بهاء ع ح ع

Feb 21, 2019

good

por Rafat A A

Sep 27, 2017

good

por Zahid A K

Aug 24, 2016

This

por Albert B F

Jun 11, 2017

H

por Phoukhong P

Jun 30, 2019

I like it very much. The web interface for learning are upgraded for better navigation and view!

por Alexander D

Jun 21, 2020

Some of the lessons don't make sense and need more explanation

por Henry M M

Mar 01, 2017

Good

por April H

Dec 26, 2017

This course contains a good amount of information for intermediate GIS users, but it repeats too much material from the previous courses and the presentation of the material could sometimes be organized better. The remote sensing section is actually information-dense and overwhelming, and I'm disappointed that spatial statistics wasn't covered in more detail. Overall, I think the people who would get the most out of this class are those who are interested specifically in learning basic information about remote sensing and/or automation in ArcGIS.

As a sidenote, while the instructor does a very good job of simplifying concepts that not all students may have experience with, he for some reason feels the need to reassure his audience that he isn't going to delve into the difficulties of math. I think he should mention the bounds of the class without implying that math is prohibitively difficult; people only think math is hard because others make it seem so, and we shouldn't discourage people from learning more.