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Welcome to the course audience dressed up for spatial data analyses in this lecture I will quickly introduce
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myself to you.
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Tell you why you should be taking this course and then quickly describe the different sections and topics
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being covered in this course.
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So firstly Hi I'm Minerva I'm a Ph.D. graduate from Cambridge University at Cambridge.
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I specialized in tropical ecology and extensively focused on building data science and machine learning
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models in addition to that I've devoted several years of my life cutting out spatial data analyses and
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geo processing and GISS analyses using Aag GISS among other tools.
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I've authored several peer reviewed publications and well-regarded journals.
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I have extensive experience of gathering out both advanced and basic tasks in objects and that ranges
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from simple data visualization to implementing interpellation models.
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I also holding them through in geography from and why men in geography and women from Oxford University
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you can always follow my updates at me now of date lab or manera and underscored that I live on Twitter.
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I post a lot of material pertaining to Delius spatial data analyses machine learning and it's quite
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a good collection of Maldivian and discussion.
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So why should you be learning on Geo's desktop simply this is the most important Jiajia software.
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So if you want to work in the area of genius and geospatial analyses you have to know just stop and
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you have to know how to carry out some of the most commonly encountered tasks in ageist desktop why
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you should beg the scores.
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Well it is simple.
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This course comprises of 50 plus hands on practical lectures and they will teach you how to carry out
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the most commonly encountered Geo processing tasks.
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In addition to that I will also be covering Geo statistical techniques like interpellation.
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But when I cover that topic I will not be overloading you with formulae etc..
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I would just teach you how to implement a given model and interpret the results.
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Because frankly that is what you really need to know as a first boss and everything comes later.
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So this is the most comprehensive Aag GISS based spatial data analysis course out there.
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And in this course I want Jogen as you just get ready to perform the most common tasks and countered
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by GISS analysts.
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But apart from GISS and geospatial analyses are just desktop signs use in a number of fields ecology
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Geology Geography hydrology civil engineering economics and that's just to name a few.
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Anthropologists and social scientists end up using arguments dressed up.
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So if you can collect collecting data and that has any spatial component to it then you should consider
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learning.
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Yes desktop
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after the section in section 2 I will be introducing you to the obvious interface and functionality
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you will be introduced to the different EXR products that there are are yes desktop has been manufactured.
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Yes all right.
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And after that I will be introducing you to the two components of our just desktop our map and our catalog.
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We are mostly going to be working with our map.
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But yes we are going to touch upon our catalog as well.
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You will learn how to read in and display different spatial data and ARC map.
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I will teach you how to carry out data management in our catalog including creating Geo databases that
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is very important for you because in the next lecture I've provided the tutorial data both as a Dropbox
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link and in an NGO is Geo database format.
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So if you want to read in that your data the data from the database that is something you'll have to
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learn then I will teach you basic Geo processing tasks and as a giant analyst you might be getting them
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out everyday things like making selections zooming finding values and basic measurements and also beats
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you how to change the coordinates of spatial data from one coordinate system to another.
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And after we are done with Section 2 we are going to move to Section 3 and start working with Droste
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data specifically.
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You will learn how to display raster data and GISS carry out Ruster operations things like merging bandura
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thematic reclassifying and resampling.
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I will touch upon the theory of different topographer products and teach you how to extract typography
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products for instance.
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This is a hill shade roster of a particular area in Vietnam and this has been derived from the digital
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elevation model and this is what I will fetch upon in section 3 you will be learning how to clip rosters
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using polygon shaped files as a cookie cutter extract district descriptive statistics to multiple polygons
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and dewpoints and you will also learn how to cariole dereferencing basically assigning geographic coordinates
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to image data that have no coordinates associated with them.
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In Section 4 we will be working with vector data in addition to reading and displaying ship file data.
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You will learn how to carry out exploratory data analyses and chart shape attributes you know build
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things like Bob plot's by charts to show the distribution of different attributes you will learn how
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to build plot and thematic maps to wish you realize the distribution of attributes.
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Learn to add data from other sources using spatial joins.
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And then I will touch upon some of the most common and widely encountered Geo processing tasks then
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that one ends up performing with vector data including splitting shape files clipping merging into section
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to name a few
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Section 5.
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That is a topic on basic Geo statistics and in this topic I will not bog you down with a lot of Tildy.
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It's the club at work I will teach you and teach you how to practically compute things like Euclidean
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restos which quantifies the distance to nearest vector sourses carry out density mapping.
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I will cover the theory and practical application to map the concentration of line and point vectors
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interpellation hotspot analysis to identify a statistically significant clusters of high and low values
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and you can see it in this image.
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I've actually done something similar carried out the hotspot analyses and this is what you'll learn
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about and learn how to interpret a map like this geographically weighted regression to build explanatory
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models.
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And finally we will touch upon the model builder which will show you how to automate some of the most
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common G.O. processing tasks in our genes.
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Finally we will come to Section 6 and that is the mapmaking section and you will learn how to put together
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different spatial data components to build maps that you can share with your users and readers.
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But before we jump onto all that in the next lecture I will cover some of the basic spatial data concepts
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that you should be familiar with and in case you are not.
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We'll just briefly touch upon those in the forthcoming lecture.
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