Week 6: Final project, An Unsupervised Classification of Lake Tahoe Basin Land Use/Land Cover

Hello all, this is my last post for a while since I won't be taking another GIS class until the fall next year. 
My task:

The Lake Tahoe basin has been subject to many fires over the past few years and the Forestry Department is interested in seeing how much of the south western portion of the basin has been affected in the past 20 years. However, the Forestry Department realized that they do not have LULC data for 1999. I have been tasked with performing a LULC analysis of the Lake Tahoe region in order to assist land managers with identifying the amount and pattern of forest within the California portion of the Lake Tahoe basin. I have been provided Landsat 7 data from 1999 in order to complete this analysis.

Imagery Utilized:

I used the provided landsat_img_nad27.img which contains an 8-bit Landsat 7 ETM image with 6 bands of the Lake Tahoe Basin and was taken 04-15-1999. Meaning that this image has very radiometric and spectral resolution. The image’s projected coordinate system is NAD 1927 UTM Zone 10N with a projection in Transverse Mercator. The image’s geographic coordinate system is GCS North American 1927 with a spheroid of Clarke 1866. The image was sourced through UWF’s GIS Drive however it could also be sourced through the USGS Global Visualization Viewer (GloVis).

Project Outcome:

I created one map that illustrated everything I needed to at once. With a little knowledge of mountainous landscapes, I created 8 categories for the image: bare land, coniferous forest, grass, mixed forest, scrub brush, space forest, snow and water. Everything is pretty much self-explanatory but I personally consider mixed forest a mix of trees, scrubs, grass and sometimes snow or sparse forest.

The area of my study area is 62487.78 Hectares. And the percentage of land cover is as follows:

•                    Bare Land: 8717.7 hectares, 13.9%

•                    Coniferous forest: 11444 hectares, 18.3%

•                    Grass: 1455.5 hectares, 2.3%

•                    Mixed Forest: 8091.3 hectares, 12.9%

•                    Scrub Brush: 6281.3 hectares, 10.1%

•                    Sparse Forest: 11025.7 hectares, 17.6%

•                    Snow: 7029.21 hectares, 11.4%

•                    Water: 8463 hectares, 13.5%

My concerns for this project are that the image of the area that is photographed is taken in April which is a time of year that still has snow on much of the mountains. So it is possible that the areas categorized may change in a few weeks to months. It is difficult to tell the difference between what could be dense scrub brush and grass, mixed forest and scrub brush, and barren land can sometimes be as white as snow. Not only that but the greenery is often sparkly forested or shrub brush may look like trees. Meaning that this is not entirely perfect as mountain landscapes are very complex, that I am not a professional and these are just the numbers I got doing my best work.

Another thing is that I chose this particular area because I started trying to classify the entire image and ran into several issues where urban was also snow, grass was also water, sage wasn’t really showing up as its own thing. So to avoid the urban area and the issues it presented I chose this chunk of land and made a partially true story. The area is under conservation and there have been many fires which has affected the land and caused fine sediments to drain into the lake due to small amounts of desertification caused by fires. The U.S. does seem to make a yearly GIS maps based on areas impacted by fire, conservation issues, protection plans, land use and many other subjects. I am sure that they have a 1999 LULC map of the area but I wanted this project to be all my work and not use their data as a crutch.

Map:

It is below and I hope that it is as self-explanatory as can be. The large mage on the left is my unsupervised classification of land use and land cover for Lake Tahoe’s basin. The inset map is to show the original true color landsat 7 image and the images as well as the study area’s location in terms of the United States Map because it is one thing to say Lake Tahoe but not everyone knows where it is located exactly or that it is in two states. The scale bar for my LULC image is to the bottom left because it didn’t look ok anywhere else and the north arrow is in the lake itself so it didn’t conflict too much with my map. I feel like I should have added the area of each classification but it just made the map look too clustered.

Week 5: Supervised Classification

Hello all!
This will be a short explanation because I have been burning the candle from both ends for several days and I'll soon crash.
So this week I preformed a supervised classification of land use for Germantown, Maryland using Erdas and its supervised tool.
An AOI image was added to the provided aerial image, and using a mix of the Inquire (legacy) cursor, region growing properties tool, signature editor, offered coordinates and classifications, a heavy dose of eyeballing and referring to examples classified the land use. Then I recoded the classes to be a single number, re-added the names of the classes that correspond to the number, and add area.
It sounds easy but between being so tired and being slightly unsure if I was doing things right I re-did and deleted things several times until I was satisfied. Which only took 7 hours just for the last exercise before I transferred the image to Arc GIS Pro and created the map which is below.

Week 4: Image Preprocessing

Hello all,
 This week ERDAS Imagine was used to process and look at a raster image and identify 3 different aspects of said image.
Feature 1: Using the inquire tool I found that a spike in pixels between 12 and 18 in Layer_4 is water. In my opinion it was easier to see the Water in the raster band combination Red: 4, Green: 3, Blue: 2, or near infrared because water shows up as a dark blue or green in this band combination whereas the land is a range of red colors.
Feature 2:  Using the inquire tool and histogram I found that Snow on the mountain had small spike in layers 1-4 around pixel value 200, and a large spike between pixel values 9 and 11 in Layer_5 and Layer_6. I used the  raster band combination 1, 1 , 1 or grey scale to make the brightness in the pixel values to shine through the most.
Feature 3:Using the inquire tool and histogram I found that the water of a small lake has much higher pixel values in layers 1-3 while layers 5 and 6 remained relatively unchanged. I used the true color combination or Red: 3, Green: 2, Blue: 1 to make the bright blue reflection of the lake to be seen the easiest.

After these features were found I created a subset of the image then imported the images to create a map for each of the features in Arc GIS Pro which are below.

Week 3: Intro to ERDAS

Greetings on this chilly blustery day,
So this week was an introduction to ERDAS Imaging 32 bit. It was not all that bad for a first time, the interface reminded me of windows 64 a little bit but it functioned pretty smoothly. I can't say that I like the little round about ways to save or work on things but I like the save session option. I can see its applications and favor ability but it will take a while to get used to the new program.
The task this week was to navigate around ERDAS and get comfortable with the program. Then take a provided raster image, edit the bands to be a TM false natural color band combination, add an area column to the attribute table then crop the image to size using the inquire option, that the image and export it to Arc GIS Pro and make a map with legends for area size and colors.
This is said map.

Week 2: Land Use/Land Cover

Hello again,
       This week was about land use and land cover where I took a provided image and made a feature class (LULC) to create polygons in order to class II classify the land usage of the image using ArcGIS Pro. The levels were as follows: 

1. Urban or built up land
1. 11: Residential
2. 12: commercial service
• 129: vacant
3. 13: Industrial
4. 14: Transportation, Communications, and Utilities
2. Agricultural Land
1. 21 Cropland and Pasture
3. (4)Forest Land
1. 41 Deciduous Forest Land
4. (5)Water
1. 51 Streams and Canals
2. 52 Lakes
3. 54 Bays and Estuaries (did not have enough time)
5. (6)Barren Land
1. 73 Sandy Areas other than Beaches

After the digitizing and categorization was done I created a point shape file to plot points at semi-random to check for accuracy. My method was kind of used a grid where I went left to right and clicked at random on that line motion. Then to check I used an "in/on field" accuracy assessment using google maps street view. I was unsure how to calculate accuracy and I forgot to add the accuracy to the map. But I was unsure of the numbers anyway. If we count the water areas I did not digitize then I probably got around 60-65%, and if we ignore that I think I would say 70-75%. I may be wrong however. 

     The colors I chose to categorize was from the random assortment of bold colors with slight tweaking so green corresponded to trees and blue to wetlands and all set at a transparency of 40-50% depending on the vibrancy.

     Below is the finalized map, I probably spent too long on the digitizing but it looks good.

     Thank you for reading and hopefully you stay tuned for next week.

     ~Jo Snow. 

GIS 4035 Beginning!

Hello all,
     I am back at it again in GIS at UWF this fall with an 8 week course in Remote Sensing and Photo Interpretation. I am excited but also anxious to get back into the swing of things considering I have had 5 months to forget a lot.
     Anyway, in this week's lab (week 1) I looked at an image and then distinguished as well as labeled tone from very light to very dark, and distinguished as well as labeled texture on a scale from very fine to very coarse. This was done by using the definition of the terms and creating polygons to illustrate the areas by their term. Then, identified objects by shape and size, shadow, pattern and association on a greyscale areal image; this was done through definitions of each criteria and plotting points with labels to illustrate which criteria it falls under as well as what it is. Finally, the last objective was to see the difference between true color and false color images; this was done by identifying 5 features in true color then looking at the same feature in false color. There was no deliverable for this part.
     Thank you for reading and see you next week,
      ~Jo Snow.

Final Project Presentation

Abstract:

      I am overweight, do not like using a gym and would like to get out of the house. I am also curious about the statistics of how many Americans exercise regularly to see how I stand in the exercising realm. Using ArcGIS I would like to look at the demographics of how many adults exercise regularly in 2018, compare myself with this data, and plan a camping trip to Blackwater River State Park.

Processes that were used are: project, buffer, clip, screen digitizing with the edit tool, label (I know that is not a tool but it annoyed me and I spent a lot of time with it), and add data.
      My area of interest is Blackwater River State Park that is in Santa Rosa county, Florida. The park has 30 camping sites, restroom and shower facilities, picnic pavilions, hiking and walking trails, water and other outdoor activities. There are plenty of hiking and walking trails that vary in length available at Blackwater River State Park to spearhead my weightless goal. Using an ArcGIS living map I found that I am  on par for average exercise for Americans on the National and for my zip code scale, I am above average for the county scale and for and under average for my specific block.
      Data and information was sourced from FGDL, FDOT, Esri, www.floridastateparks.org, and floridahikes.com.
      Below is my PowerPoint Presentation for my project (The link). I hope you enjoy.

https://drive.google.com/file/d/1DrSaLgwRFIsn1dfePA4x2YAdzH2BI7hy/view?usp=sharing

Note: The linked powerpoint is honestly difficult to read and I apologize. Also for some reason when downloading to my google Drive it chopped up the work Fin on the last slide.

Week 12: Georeferencing and 3D Map

    Alright, Alright! Last lab folks! I'm excited to be done and to see how far I have come but I'm sad to see it go! And by last lab I mean the last lab with step by step instructions which leads to the next emotions I am feeling: anxiety, dread and worry. I say this because next week I have to come up with my own map idea from scratch! (crying inside)
      Anyway, about this weeks lab. So this week is about georeferencing and to quote the lab instructions it is: "also called ‘image registration’, is a process you may use to tell a raster dataset (like an aerial photograph or scanned map image) “where it belongs”. This is done by identifying a common point on the target layer and an already referenced control layer (roads shapefile, DOQQ, DRG) and linking these common points." For this lab's purpose I took two UWF aerials and clipped points, known as control points or as I like to think of as snap points, from the image to the corresponding UWF building layer in order to sync the image with the buildings, and by proxy, roads layer. After that was done I had to digitize or trace the outline of (in the aerials) building 72 which was new Health Leisure and Sport Facility. This was done because building 72 was the only non-digitized building in the feature class. Once that was done it was of course added to the attribute table and labeled as necessary. This was repeated with Campus Lane, a road that was not digitized for the UWF roads layer. Then I made a two ring buffer zone of 330 and 660 feet respectively for an eagle nest on campus and linked a picture from my google drive to the map to see the nest. (pretty sure I forgot to add the link to the final map itself) Once that was done I was free to go crazy and create the lovely map I am going to include below.
     Now that this map was created I was prompted to create a 3D Local scene, and let me say this was sooo cool to see. I used the LAS dataset to raster tool to turn the LAS dataset UWF_Lidar.lasd into an output raster UWF_DEM. The lab then prompted me to alter a few settings of the local scene before allowing me to make the second map I am including. It was a little tight to add things but I think it looks pretty pleasing to the eyes.
     Well that is all I have to say about this lab. I will be posting for what may be the last time in the next 2-3 weeks for my final in Intro to Gis Lab. Hope everything goes well for everyone and anyone who reads this!

Week 11 Geocoding and Network analysis

This lab was engaging, it made me refer to the discussion board at least 5 times because some things in the lab instructions were not clear or incorrectly labeled. To put it simply this lab we learned to geocode 21 EMS locations and make a route between three of them, map the locations with proper locations and then make a final map. We used the project tool, create address locator tool, geocoding tool (pick the address tool), network analysis and then made a route tab.  I don't know what else to say because my map kinda sums itself up.

Week 10 Vector Analysis

Hey look guys, I got another lab on time! It is probably stupid but I truly am proud at how the maps I make look. While the labs take time, they are becoming something I look forward to doing. The processes are becoming increasingly comfortable. I can't say I exactly know what I am doing most of the time but I enjoy the work and the end product. It is hard not to spend too much time on the aesthetics of a map sometimes.
Anyway, this week's lab was intended for us to learn how to take vectors and analyze them with different tools. This lab we used Buffer, Overlay, Buffer analysis, Python, Multipart to Singlepart, Erase, and learned how to add adding fields to attributed tables then assigning them values.
As the map shows this is a map about the possible campsites in DeSoto National Forest, Mississippi. It shows lakes, rivers, roads, conservation areas and campsites. However each of these attributes are limited to the parameters listed. Honestly that is all I have to say about the map to be honest.
Hope you have a nice day!

Week 7 and 8: Data Soul Search

Hey look at me, got another lab done on time. This lab was fun, very fun but time consuming. I spent a total of 18 hours searching for data, editing and making maps. Those numbers are probably overkill but I spent every free time I had on campus (also skipped class yesterday and today to make sure I got done but that is ok because I have the notes) to make sure these maps are as good as I could get them.
I am very proud in how they look and came together. There were hours of editing and decision making to decide the best way to put them together and make them look. (I also started downloading the data for a different county for the first hour and a half.) A lot of things were tweaked, removed and added. I honestly cannot remember each step so this is going to be to the best of my ability to convey my steps. Also when I say map frame followed by a number, it is most likely not done in that exact numerical order as I added and deleted a lot of map frames. I took a great deal of time to re-remember and look up how to do much of these steps from previous labs as well as research in ArcGIS help. I bugged poor miss Diedra at least 5 times. These steps are also simplified as each day that I worked I changed my mind a lot on the layouts of things as well as text styles. I think I saved over the layout of the overview map at least 10 times. Not only that a few times ArcGIS crashed and I learned to save OFTEN.
(Yes this is taken from my process summary because it is the best I could explain the process of how I made these maps to others.)

1.) Downloading:

1.   Following the steps outlined in week 5’s lab I found and downloaded the north east DOQQ of quad 5241.
2. To get the rest of the vectors I used FGDL to search, download and extract the data needed for the maps.

2.) Overview map:

1. 1.      To map 1: I made a layer of Calhoun County using the skills learned in step 4 of own your own map, then removed the layer of the Florida counties
2.  Then I added cities and towns, major roads, public lands and hydrology filed to the map, then editing each layer to be to the shape and extent of the county boundary
3. I went into the attribute table of major roads and selected the state roads and made a separate layer so that I could distinguish the difference between the major state roads and the other major roads, edited the layer in the symbology to be different and tweaked the labeling to make it how it looks
4. I took time to edit the cities and towns as well as public land symbology to look like it does
5.  In map 2: I added the Florida boundaries then copied the layer of Calhoun county to the map and changed the color, this map was used as the insert map to show the location of Calhoun county in Florida for the rest of the layout maps
6. In a third map I added the DOQQ, then copied the cities and town layer I edited as well as major roads, highways and public lands layers to the map, this was used as the insert of the aerial to the overview map
7. I inserted a new layout and added these three map frames to the layout. Briefly I added the DOQQ aerial to the map in order to draw a rectangle to show its position before removing the areal.
8. To this layout map I added the legends, north arrow, title, scale, lines to connect to the aerial, map information such as my name, borders, shadows, and backgrounds and tweaked the fonts and sizes until I was satisfied.
9. This layout map is in Albers Conical Equal Area because as the lab instructions suggested, that is what the data decided. I figured that if all of the data is in the same projection and coordinate system that it is the best to map the area and distances with the least exaggeration. 

3.) Elevation Map:

1. To a new map frame 5: Following the steps for the DEM for USGS, I found and downloaded USGS_NED_1_n31w085_ArcGrid and USGS_NED_1_n31w086, re-projected them to be in the Albers conical equal area projection system to fit the rest of the data, mosaicked them together using the mosaic raster tool (and the help of Deidra)
2. Once the raster was re-projected and mosaicked I copied the layer of Calhoun county from map frame 1 and pasted to use in the next step
3. With the help of the wonderful Deidra, then used the Clip (data management) tool to clip the raster to the shape (or as close as I could get it) of Calhoun county.
4. I copied the labeled and symbolized cities, major roads, and highways to the map frame 5 in order to give references to location. I thought a map with just elevation of the county didn’t offer as much as one with landmarks such as roads and towns.
5. I symbolized the elevation colors to one that is understandable and decent looking, unlike the grey scale it came in.
6. Then I added map frame to a new layout, as well as map 2 to be the insert map
7. To this layout map I added the legends, north arrow, title, scale, map information such as my name, borders, shadows, backgrounds and tweaked the fonts and sizes until I was satisfied.
8. The scale bar is smaller here because it was hard to read if it clipped into the elevation map that I was unable to cleanly clip to the shape of the county
9. This layout map was also in Albers Conical Equal Area for the same reason as above.

4.) Land Cover and Invasive Plants Map:

1. In map frame 6: I added the same Calhoun county from map frame 1
2. I went into the invasive plants attribute table and selected the plants that appear in Calhoun county and made their own layer
3. To the same map frame I then added the Land Cover data.
4.  In the symbology I deleted the background information because it caused the data to not stay within Calhoun county and rather made a square around it, gave each type of category a unique color that could stand out and not be lost in the mess while also trying my best to keep to the suggested colors in Own Your Own Map
5.  I then went into the label of the categories and simplified them while keeping their same data, for example Agriculture/Pasture/Groves became Pasture and Groves Agriculture.
6. Now that I had the colors for the land use set I then went into the symbology of the Invasive Plants layer and assigned each type of plants their own symbol and color rather than a dot and name. These symbols are not usually typical for plants but I saw that they stuck out while not obscuring the map.
7.  I added map frame 6 to a new layout, as well as map 2 to be the insert map
8. To this layout map I added the legends, north arrow, title, scale, map information such as my name, borders, shadows, backgrounds and tweaked the fonts and sizes until I was satisfied.
9. Literal last minute before I had to leave lab to go home (I had lost track of time and my father messaged to say if I didn’t show up he was going to leave me) I was checking the properties of each data set to make sure that everything was in the same projected system, only to find that Land Cover was in NAD 1983 HARN Albers rather than Albers Conical Equal Area. I quickly made note of this and typed the map projection into the text box where I had the other projection systems. I tried to load the ArcGIS file in the online argo app but it did not register my flashdrive or let me access my personal computer files. I understand if this causes me to have points deducted but I at least cited that it did in fact have a different PCS.

5.) My babies:

 

(Looking at this last one I think I made two of the land cover colors the same but it was hard to keep track)

Week 6, Projections: The Sequel

     Alright! Look at me, finally getting something submitted on time, entirely completed and hopefully correct!
     This lab was a doozy. There were so many steps between downloading data, unzipping and moving files, creating a whole slew of files, re-projecting and redefining data time and time again, and even using excel.
     Don't get me wrong this was a fun lab but it was exhausting. I spent 6 hours on the lab in the GIS lab and was turning to page 20 of the lab prompt and thought I saw the  light at the end of the tunnel. Only to find that I had to redo everything from the get go and make my own map. (Now that I think about it I left off two scale bars.)
     After I got home and mustered the will to continue the assignment I spent about 5 more hours on it. Much of this time was fighting the map layout, deciding colors that could be seen and messing up re-projecting the same file many times, but mostly fighting the map layout.
     I realized by scrolling down on the rubric that I am supposed to include an image of my map but let me say that I had completely forgot and added the ones that I have to the assignment. Not only that but for some reason ArgoApps did not want to register my flash drive for a good while and then did not want me to save. I say this because I had to submit the assignment through ArgoApps instead of my usual web browser which made me unable to copy and paste this blog link, but hopefully I can comment the link to this in the assignment in a bit.
     Speaking of fighting the map layout, I was unsure what the assignment wanted as far as three views go so I decided to spend some time getting more familiar with making a map layout while I had the time to. I three maps, one that was zoomed out with the county boundaries and Quad index, one that showed Escambia county with the aerial views, plotted points of the petroleum contamination, major roads, county boundary, quad index, and a light under map to make it look nice, and then a smaller version of the second map but zoomed way in on the Pensacola quad that I chose.  I think it looks nice and I am honestly proud.
     I have to say that the class confuses me greatly, it seems like so much new information that doesn't make much sense. The labs are confusing because I don't quite know how to answer the questions. I am doing my best and would like to think that if nothing else I am getting better at using ArcGIS Pro, even when I have to flip-flop between computers.
     On the subject of what was don't this week I think I grasped the concept that I took data from varying sources, types and projections and re-projected or defined the data in a way that was uniform in GCS and PCS before bringing it all together and making a cohesive map. Not only making a cohesive map but keeping up with all the steps, questions to answer in the process summary and keeping the files and file paths coherent. I usually do a way better job making files in my computer to store things but for some reason this class threw me for a loop, but I would like to think that I am getting the hang of things. I even tried harder to keep the names in GIS format, that I forgot about, even though everything in me wants to add spaces rather than underlines and squishing things together. (I'll include the picture of the files because I am that proud.) While this was interesting I have a feeling that the next lab will rely heavily on this and I have another feeling that it wont be nice and walk me through the steps. And I am not sure if I am quite ready. However this lab is also teaching me to not be so afraid to reach out for help which I have always had an issue with being as I would rather do it myself and not have to bother anyone, but this is subject matter I have to pony up (as someone I know says) and ask.
     Anyway, thank you for reading,
     ~Jo Snow.

   

Week 5: Projections Phase One

     Before I begin I'd like to say that I somehow managed to name my files wrong but managed to keep the blog in time with the weeks. Once again late because of family issues, getting sidetracked by statistics homework and trying to own my own map. Also step 7 part 6 had me confused for a while.
     Alright, I have to say that I am really starting to enjoy these labs. Though they might be a little frustrating and stressful its so fun as someone who loves to watch processes to see the labs come together. The fact that we map makers get to personalize each finished product is addicting and easy to get carried away in. I am not quite sure if I understand the difference between PCS and GCS but I am getting there. I do however understand that different forms of projections allow and create stretching and skewing. I have been following VOX and other similar educational sources like TedEd and BBC and and actually saw the video linked in the lesson when it came out. I loved the video and enjoyed watching it again and relating what he said to what I have learned. Though this lab is late I think I enjoyed it as much as I did the last lab, which is saying something.
     While sitting here and typing this I also realized that I said that projection style as UTM 2016 instead of UTM 16 N on my map and I feel so stupid.
     Here's to hoping I can get back in line. Thanks for reading,
     ~Jo Snow.

Week 4: Data Collection

     So far this lab was the most enjoyable and engaging. It so cool to see that each step actually made the feature layer, then to plot the points and watch them actually become a part of the map I made. Plotting the points was so much fun, because I tend to take walks on campus to clear my head meaning I got to take my normal walk and get work done. Not only that everything worked as it was supposed to for once. I even started this lab early on Monday in hopes of not making it late, because I thought to my self that it was time to break a bad habit. I actually went to lab every day but Tuesday to work on this in the GIS lab. 

     When I realized that the lab was on public safety, the first thing that popped into my head were the "Blue Lights" which my family called the emergency poles. My family has been walking on the nature trail since I was very small and once I got bigger I asked what the pole was for and from then on thought that they were a very important safety precaution. I appreciate these installments of infrastructure even more since I walk almost daily on the nature trail and other areas that tend to not have many onlookers alone. I am not necessarily afraid, but the knowledge that the Blue Lights are there gives me some peace of mind. So, I did not intend to rip off the lab instructions, but once I realized that my idea of public safety measures/infrastructures worked for the lab and seemed like an easier choice I immediately jumped on the prospect and made the data collection based around the blue lights.

     The lab itself was done, all I had to do was the final step of the Process Summary where I had to reword the sharing steps. I was finally proud of myself. I even made sure to take the reading test because I had a feeling I would need to. Should have listened to that feeling and also finished the process summary as well because once I was on the way home I got bad news and then to top it all off our only car broke down and probably wont be starting again. When I Finally got home it seemed that a nap was way better than eating or anything because I didn't sleep a wink last night. This nap turned into a 7 hour nap. The only reason I woke up was because my boyfriend called me off the hook to make sure I woke up to finish the lab. Somehow slept through over a dozen calls and messages, at 11:43. Well, I got the process summary done and turned in making yet another late lab. 

     I did enjoy the lab a lot and felt like I am learning something, but hindsight is 20-20. 

     Hope whoever is reading this had a good day and such,

     ~Jo Snow. 

I am also including the story map I made for the lab, as is required the link is below. 

Story map: 

http://pns.maps.arcgis.com/home/item.html?id=60a97ac43cc243169f5e1086405b5ca5

Week 3 Cartography

Well it seems that I forgot to do this on time, I'm sure there are repercussions but it entirely slipped my mind. I have to say I almost gave up on the first step of this lab because the metadata would not show up properly, thanks to my horrid internet service. I even went to the lab to retry to unzip the folder, took three tries before I could even get it to work. However, I had to go home so I transferred the data to my little shark thumb drive in hopes that would work, it didn't. I finally figured out how to do an insert map, at least I think. Can't say how many times I spelled "Cartography" wrong though when trying to restart/create a new project in hopes that the files unzipped wrong. Overall the lab, while stressful, is so interesting to see how things build on each other. Kinda excited to see what the next lab entails.

Week 2 Arc Own Your Own Map

     Hello to whomever has decided to read my word vomit of a blog. While this assignment was named "Own your own map" it seems like the map owned me.
     Since two days before school started things have been going on in my family. I am doing my best to keep on track and not need any leeway or sympathy because this is just the start, but boy is it rough some days. So if my kind professor is actually reading this, though I have no idea why she would want to read my nonsense, I have not specified what has happened because I am almost certain that things will get far worse than they currently are and I do not want to expend her kindness or leeway before I truly need it.
     I will just have to work harder to push the troubles away and focus as I can not allow this to derail me. I will do my best to not make it habit to turn things in late, maybe the same day or pretty close to the deadline but I truly hope I do not make a fool of myself. Its not that I don't care about the class, or treat it as something less than but my family dynamics are difficult and chaotic to say the least.
     Alright, who knew it was possible for file explorer to crash and you be completely unable to access your files or save? Well if you didn't, now you do and if you did, good for you. It took 10 minutes of solid panic to see if I didn't unknowingly ruin my computer to resurrect the process. Restarting the computer 5 times, ending and restarting the process in task manager and trying to access the process another way did not work. I got on my mothers phone to look up videos on how to fix it because oddly enough the wifi went out and I forgot to buy data. Anyway, seems that technology had it out for me this evening.
      The assignment itself was interesting to see how things built on each other and then made a pretty map that I always wondered how was made. I had to fight myself to not make everything varying shades of soft blue and purple and light grey for some reason.
     As I said for the answer to my post assignment: "My map is incorrect because I was unable get the Florida Overview map and the UWF main Campus map to be separate maps then join them together on one layout. Due to this the star of UWF and the City label show up on the small Florida Overview map because they were the same exact map, just zoomed to different layers and would not allow selecting things differently. That is my fault and I will practice after I submit this to learn how to do it correctly. I chose the colors as close to the assignment as I could, even though for some reason I was leaning towards purple and grey today. I chose the scales I did because they seemed to be the only ones that wanted to work with me and display the correct numbers. I chose to do the layout because it seemed to be the most sensible and because when I got to the end of the instructions I was able to see how you demonstrated it and moved things closer together." Yes even the scales did not want to report the correct numbers, but that is probably because I was mildly freaking out.
      I will not let this derail me and will do my best to practice more and learn how to do this correctly. It truly interests me and I want to learn. Not quite sure if this is not appropriate for a school/professional based blog post but I can edit later if necessary.
     Thank you for reading. I hope everyone had an easier time than I did and enjoyed the lab. Have a wonderful weekend to all. Interesting fact: babies are born with more bones than adults to fit through the birth canal easier, these bones later. But they are born without kneecaps.
     Who wants to own their own map when the map can own you?
     ~Jo Snow.

Week 1 Lab: ArcGIS Overview

     Hello all, I have never even visited a blog let alone used one so bear with me here.
     This lab was rough. My wifi was rather rough and I had to complete the lab today or I wouldn't have at all. The newness of the format, information and software, along with my failing internet connection, caused me to restart the lab from the beginning a total of 4 times. That being said, there is no guarantee that my tired self completed the assignment correctly. Family circumstances have dictated that I will not be in town after tomorrow morning and until the due date, so here I am at 4 in the morning posting this. I have to say that the software we use is rather interesting and set up much like Microsoft word. It will surely take some getting used to. I think the hardest part will be following the lab instructions and getting everything correct, however, it seems that the lab manual is rather well laid out. This will certainly be a learning experience, lets see how this goes.
      Good luck all and than you fro reading.
      ~Jo Snow.