Python: Geospatial Environment Setup (Part 1)

The devil in the details

I have started to post some videos demonstrating some tools in ArcGIS Pro. Short ones and pretty quick ones which I strived for since I absolutely am frightened with the idea of irritating people with unnecessary voice-over. It has no garnered much response and it's cool with me. Although, the lack of traction does things to my insides, I go back to the real reason I am doing thing, which is to stash the tools that I managed to learn on my own by trials and errors and keep them somewhere I can refer back to it to remember how it works.

Creating maps involves a number of iterative processes made to suit the intended output. Although creating maps itself is a form of art; heavily reliant on target audience's knowledge and aesthetical preference, it is still an inherently democratic science. Thus, knowing the mainstream technology and tools in the industry to express your vision or message is given. So for those just starting out with using geographical information software (GIS) for your final year project or research, this videos are meant for you. The purpose is not to overwhelm you with too many information, or distract you with my narration, but to follow in real-time the process from the start up of the software to the running of tools that generates the information needed.

Knowing fully well that there is an endless variety of GIS software or tools out there, processes that you need to execute to make things happen may vary in name and functionalities. Forget the beef between ArcGIS and QGIS, of which one is the better tool; if it serves your needs, then use it. You're not obliged to pledge loyalty to software or brands although you are encouraged to maintain integrity in your beliefs when it comes to corporate versus open source tools in the industry. Both choices come with their advantages and disadvantages. Yours truly uses QGIS and ArcGIS Pro interchangeably. If it doesn't work in ArcGIS Pro, which I use primarily, I'll jump to using QGIS. It's not a big deal. If it works painlessly, there is no reason to feel bad about using it.

So far, the content I have made emphasizes mostly on ArcGIS Pro or Esri products since using them is how I come to learn more about geology and geography. QGIS was a name I did not learn of in my university years when ArcGIS versions start with the digit 9️⃣, so you can catch my drift.

We can go on and on about theoretical stuff and our smarter pals usually knows what to do when faced with the tools. Unfortunately, I fall in the percentile that needed to land on the job to understand what on earth I am supposed to do. This series of videos are for those who have the same problem as I do and need to see the magic actually happening before knowing what to do. And for the most part, there are so many things to read and try out before you get it right. So hopefully, the demos can kickstart some thoughts or observation in the logic within the software's ecosystem and become more than just a technical power-user.

This week, I touched on some tools that I found helpful when dealing with point vector data, so feel free to check it out 👇🏻

Next week, I'm thinking of exploring some series of point analysis and space time cube is beckoning for me to test it out. Until then, stay cool and drop a word if you need any clarifications on the demos!

Society of Conservation GIS Scholarship Award 2020

Python: Geospatial Environment Setup (Part 2)

Python: Geospatial Environment Setup (Part 2)

Hey again folks! I am here for the second part of Python environmental setup for a geospatial workspace. I published the first part of this post two weeks ago. So if you've not yet read that, I'll catch you up to speed with our checklist:

Install Python ☑

Install Miniconda ☑

Install the basic Python libraries ☑

Create a new environment for your workspace

Install geospatial Python libraries

🗃 Create a new environment for your workspace

Since we have actually manually set up our base environment quite thoroughly with all the basic libraries needed, to make our work easier, we can just clone the base environment and install all the additional essential libraries needed for geospatial analysis. This new environment will be called geopy. Feel free to use a name you identify most with.

Why don't we just create a new environment? Well, it means we have to start installing the Python libraries again from scratch. Although it is no trouble to do so, we want to avoid installing so many libraries all at once. As I mentioned in Part 1, there is always a risk where incomplete dependencies in one library will affect the installation of other libraries that you intend to install in one go. Since we already have a stable and usable base environment, we can proceed to use it as a sort of pre-made skeleton that we will build our geospatial workspace with.

1️⃣ At the Anaconda Command Prompt, type the following:

2️⃣ Press Enter and the environment will be clone for you. Once it is done, you can use the following command to check the availability of your environment 👇🏻

You should be able to see your geopy environment listed along with the base environment.

👩🏻‍💻 Install geospatial Python libraries

Here we will proceed with the installation of a few geospatial Python libraries that are essential to reading and exploring the vectors and rasters.

🔺 fiona: This library is the core that some of the more updated libraries depend on. It is a simple and straightforward library that reads and writes spatial data in the common Python IOs without relying on the infamous GDAL's OGR classes.

🔺 shapely: shapely library features the capability to manipulate and edit spatial vector data in the planar geometric plane. It is one of the core libraries that recent geospatial Python libraries rely on to enable the reading and editing of vector data.

🔺 pyproj: is the Python interface for the cartographic projections and coordinate system libraries. Another main library that enables the 'location' characteristics in your spatial data to be read.

🔺 rasterio: reads and writes raster formats and provides a Python API based on Numpy N-dimensional arrays and GeoJSON.

🔺 geopandas: extends the pandas library to allow spatial operations on the geometric spatial data i.e shapefiles.

💀 As you might have noticed, we won't be doing any direct gdal library installation. It's mainly due to the fact that its installation is a process that seems to be accompanied by misery at every turn and involved workarounds that are pretty inconsistent for different individuals. Does it mean that we won't be using it for our Pythonic geospatial analysis? Heck no. But we will be taking advantage of the automatic dependency installation that comes with all the libraries above. The rasterio library depends on gdal and by installing it, we integrate the gdal library indirectly into our geospatial environment. I found that this method is the most fool-proof. Let's proceed to the installation of these libraries.

1️⃣ At the Anaconda Command Prompt, should you start from the beginning, ensure that your geopy environment is activated. If not, proceed to use the following command to activate geopy.

Once activated, we can install the libraries mentioned one after another. Nevertheless, you also have the option of installing them in one go directly using a single command 👇🏻

💀 geopandas is not included in this line-up NOT because we do not need it. It's another temperamental library that I prefer to isolate and install individually. If gdal is a rabid dog...then geopandas is a feral cat. You never know how-when-why it doesn't like you and forces a single 10-minute installation drag to hours.

3️⃣ Once you're done with installing the first line-up above, proceed with our feral cat below 👇🏻

4️⃣ Use the conda list command again to check if all the libraries have been installed successfully.

🎉Et voilá! Tahniah! You did it!🎉

🎯 The Jupyter Notebook

It should be the end of the road for the helluva task of creating the geospatial environment. But you're going to ask how to start using it anyway. To access this libraries and start analyzing, we can easily use the simple and straight-forward Jupyter Notebook. There are so many IDE choices out there but for data analysis, Jupyter Notebook suffices for me so far and if you are not familiar with Markdown, this tool will ease you into it slowly.

Jupyter Notebook can be installed in your geopy environment as follows:

And proceed to use it by prompting it open via the command prompt

It ain't that bad, right? If you're still having problems with the steps, do check out the real-time video I created to demonstrate the installation. And feel free to share with us what sort of problems you have encountered and the workaround or solutions you implemented! It's almost never a straight line with this, trust me. As mentioned in the previous post, check out the quick demo below 👇🏻

See you guys again for another session on geospatial Python soon!

Python: Geospatial Environment Setup (Part 2)

Hey again folks! I am here for the second part of Python environmental setup for a geospatial workspace. I published the first part of this post two weeks ago. So if you've not yet read that, I'll catch you up to speed with our checklist:

Install Python ☑

Install Miniconda ☑

Install the basic Python libraries ☑

Create a new environment for your workspace

Install geospatial Python libraries

🗃 Create a new environment for your workspace

Since we have actually manually set up our base environment quite thoroughly with all the basic libraries needed, to make our work easier, we can just clone the base environment and install all the additional essential libraries needed for geospatial analysis. This new environment will be called geopy. Feel free to use a name you identify most with.

Why don't we just create a new environment? Well, it means we have to start installing the Python libraries again from scratch. Although it is no trouble to do so, we want to avoid installing so many libraries all at once. As I mentioned in Part 1, there is always a risk where incomplete dependencies in one library will affect the installation of other libraries that you intend to install in one go. Since we already have a stable and usable base environment, we can proceed to use it as a sort of pre-made skeleton that we will build our geospatial workspace with.

1️⃣ At the Anaconda Command Prompt, type the following:

2️⃣ Press Enter and the environment will be clone for you. Once it is done, you can use the following command to check the availability of your environment 👇🏻

You should be able to see your geopy environment listed along with the base environment.

👩🏻‍💻 Install geospatial Python libraries

Here we will proceed with the installation of a few geospatial Python libraries that are essential to reading and exploring the vectors and rasters.

🔺 fiona: This library is the core that some of the more updated libraries depend on. It is a simple and straightforward library that reads and writes spatial data in the common Python IOs without relying on the infamous GDAL's OGR classes.

🔺 shapely: shapely library features the capability to manipulate and edit spatial vector data in the planar geometric plane. It is one of the core libraries that recent geospatial Python libraries rely on to enable the reading and editing of vector data.

🔺 pyproj: is the Python interface for the cartographic projections and coordinate system libraries. Another main library that enables the 'location' characteristics in your spatial data to be read.

🔺 rasterio: reads and writes raster formats and provides a Python API based on Numpy N-dimensional arrays and GeoJSON.

🔺 geopandas: extends the pandas library to allow spatial operations on the geometric spatial data i.e shapefiles.

💀 As you might have noticed, we won't be doing any direct gdal library installation. It's mainly due to the fact that its installation is a process that seems to be accompanied by misery at every turn and involved workarounds that are pretty inconsistent for different individuals. Does it mean that we won't be using it for our Pythonic geospatial analysis? Heck no. But we will be taking advantage of the automatic dependency installation that comes with all the libraries above. The rasterio library depends on gdal and by installing it, we integrate the gdal library indirectly into our geospatial environment. I found that this method is the most fool-proof. Let's proceed to the installation of these libraries.

1️⃣ At the Anaconda Command Prompt, should you start from the beginning, ensure that your geopy environment is activated. If not, proceed to use the following command to activate geopy.

Once activated, we can install the libraries mentioned one after another. Nevertheless, you also have the option of installing them in one go directly using a single command 👇🏻

💀 geopandas is not included in this line-up NOT because we do not need it. It's another temperamental library that I prefer to isolate and install individually. If gdal is a rabid dog...then geopandas is a feral cat. You never know how-when-why it doesn't like you and forces a single 10-minute installation drag to hours.

3️⃣ Once you're done with installing the first line-up above, proceed with our feral cat below 👇🏻

4️⃣ Use the conda list command again to check if all the libraries have been installed successfully.

🎉Et voilá! Tahniah! You did it!🎉

🎯 The Jupyter Notebook

It should be the end of the road for the helluva task of creating the geospatial environment. But you're going to ask how to start using it anyway. To access this libraries and start analyzing, we can easily use the simple and straight-forward Jupyter Notebook. There are so many IDE choices out there but for data analysis, Jupyter Notebook suffices for me so far and if you are not familiar with Markdown, this tool will ease you into it slowly.

Jupyter Notebook can be installed in your geopy environment as follows:

And proceed to use it by prompting it open via the command prompt

It ain't that bad, right? If you're still having problems with the steps, do check out the real-time video I created to demonstrate the installation. And feel free to share with us what sort of problems you have encountered and the workaround or solutions you implemented! It's almost never a straight line with this, trust me. As mentioned in the previous post, check out the quick demo below 👇🏻

YouTube

🌏 Python: Geospatial Environment Setup 🎉

A deconstructed time-lapsed Python geospatial environment setup with `conda` from downloading necessary software to loading the Jupyter Note

See you guys again for another session on geospatial Python soon!

[2022] 30 Day Map Challenge -- FAILED

Last year, I participated once again in the 30 Day Map Challenge that was going around in Twitter-ville come November. It is the 3rd attempt at the marathon and 2022 served as a reminder that progressed too despite getting stuck at Day 3 as life caught up with me.

I don't like the idea that I have left the challenge incomplete, again. It was not my priority and I work better with clear goals or visions of expected output. If it does not add to my need to learn something new ...it will be a task bound to head straight to the backburner. Let's resolve to make it a long-term routine instead of a spurt of stress trying to make the deadline.

As a consequence, I am attuning this task into one that actually gives me the benefit out putting into record the techniques and tools I used to make the maps in writing. I believe that will serve more purpose and added value other than visuals. And perhaps, have some stock ready for submission this year instead.

Anyone else participated in this challenge back in November? How did you do and what would you like to do better for the next one? Don't be shy and do drop a word or two.

There is a moment where base maps just couldn't or wouldn't cut it. And DEMs are not helping. The beautiful hillshade raster generated from the hillshade tool can't help it if the DEM isn't as crisp as you would want it to be. And to think that I've been hiding into hermitage to learn how to 'soften' and cook visual 'occlusion' to make maps look seamlessly smooth. Cartographers are the MUAs of the satellite image community. 

I have always loved monochromatic maps where the visual is clean, the colors not harsh and easy for me to read. There was not much gig lately at work where map-making is concerned. The last one was back in April for some of our new strategy plans. So, when my pal wanted me to just 'edit' some maps she wanted to use, I can't stop myself with just changing the base map. 

The result isn't as much as I'd like it to be but then, we are catering the population that actually uses this map. Inspired by the beautiful map produced by John M Nelson that he graciously presented at 2019 NACIS; An Absurdly Tall Hiking Map of the Appalachian Trail. What I found is absurd is how little views this presentation have. The simplicity of the map is personally spot-on for me. Similar to Daniel P. Huffman as he confessed in his NACIS 2018 talk; Mapping in Monochrome, I am in favor of monochromatic color scheme. I absolutely loathe chaotic map that looked like my niece's unicorn just barf the 70s color deco all across the screen. Maybe for practical purposes of differentiating values of an attribute is deemed justifiable but surely...we can do better than clashing orange, purple and green together, no? 

So...a request to change some labels turn into a full-on make over. There are some things that I realized while making this map using ArcGIS Pro that I believe any ArcGIS Pro noob should know:

Sizing your symbols in Symbology should ideally be done in the Layout view. Trust me. It'll save you alot of time. 

When making outlines of anything at all, consider using a tone or two lighter than the darkest of colors and make the line thinner than 1 pt. 

Halo do matter for your labels or any textual elements of your map.

Sometimes, making borders for your map is justifiable goose chase. You don't particularly need it. Especially if the map is something you are going to compact together with articles or to be apart of a book etc. 

Using blue all the way might have been something I preferred but they have the different zonations for the rivers, so that plan went out the window. 

And speaking of window...the window for improvement in this map is as big as US and Europe combined. 

Yes peeps. I’ve been studying and on contrary to all my previous attempts to make beautiful notes, I say f it and just work with what helps me clear my head the fastest 🏃🏻‍♀️. I love writing notes, but I realize, to gather my thoughts properly, I need some sort of way to not waste paper just to arrange and rearrange my ideas or comprehension of things. 

What better way of doing that than using a mind map!

So you kiddos out there who are starting out with Python and just can’t wait to get into deep learning or machine learning, I’d say, hold your horses for a minute and have some preview of that pond you’re trying to jump into. And don’t be scared, cause we’re all friends here in the hell-hole of learning plateau. Will it get better? I believe so. I am positive I understand more of the principles of deep learning and the relevance of Python libraries associated with it. Yes...this is a Python bar, darling. 👩🏻‍💻

There’s no real shortcut if you ask me since we have different way of comprehending things; my pre-existing mold may have harder time grasping the things I am learning right now than you would. So don’t be afraid to doodle while you think. No amount of paper will be enough to help you understand things, so better start being sustainable by using some digital platforms and saving those papers to when you’re truly ready to pen out your understanding of things; not what you read. There’s a difference!

Check out the mind map of some essential Python libraries you can get started with before you start doing some deep learning. It’s worth reviewing all that prior, I promise. 

Have fun! 🙆🏻‍♀️

Taskade: Multi-platform planner and task manager

The year 2021 is looming over us and I am dying to have some sort of control over what I could be doing for the next 365 days. While 2020 had been a year of 'character building', I discover alot of things about everything around me and myself. For starters, I am an avid planner; surprisingly. But it does not mean that I follow through with them. See what I did right there? I am admitting the truth behind self-study and lifetime of learning.

With alot of things I have planned to breathe new life to my own progress and time management, I went hunting for some interesting stuff in the internet for inspiration and try-outs. And guess what? I found one and I think most people may have been using this already in full swing because the review is 5 ⭐!

🌑🌒🌓🌔🌕🌖🌗🌘🌑

Taskade is simply a project/team management tool. Ah ah ah...before you write me off, hear me out. Taskade is aimed to help teams to plan, organize or manage their tasks and prioritize output for decision-making. It is simply an interactive planner sans organizer sans dashboard that sees where you're at with your work, what you've managed to get done and communicate tasks among people in your team; IF you have a whole team working on some sort of project. Hence, the chat capability that is implemented in this tool.

At my job, I work in a team of only 2 people; me and another colleague, and we're the regional programme unit which is apart of the bigger unit of team mates spread elsewhere in other regions. So, just because your unit is small, it doesn't mean that your task load complements your pint-sized manpower. So, I've been looking for platforms that could help me organize our productivity and ensure high-quality output. Just because technology is more advanced, it doesn'e mean there isn't any learning curve, right? So I tried just about anything under the sun for project/team management; Asana, Slack, Discord, the pre-existing Google..., but none of them could nail all shortcomings precisely; due dates, assignment of tasks, progress, sub-tasks, interactive commenting, multiplatform sync, brainstorming etc. Channels in Slack gives me headache -- same with Discord, and Telegram channels is too 'static' and 'one-way street' for me to view everything.

I found Taskade after trying to find a complementary 'Forest: Focus' extension at the Google Chrome extensions marketplace. There are plenty of interesting high-quality extensions as of late and I am pleasantyl surprised because earlier this year, most of them were quite 'beta' in their functionality. I saw a 'Bullet Journal' extension that someone raved about and another individual commented: 'Isn't this Taskade?'. The curious cat I am, I googled it and was not disappointed. What are the main keywords that hooked me?:

FREE

Google-integrated

Remote work environment advocacy

Multi-platform

What features do Taskade actually have? ✨

Given that it is an All-in-One Collaboration tool, it is understandable if the GUI is pleasing on the eyes. I do understand that first-impression is everything; color, packaging, fore-front information and visual, but it was really the functionality that delivers me to salvation. If you're an active member of Dev.to, then you'll catch feels with this theme that Taskade delivers. Key features in Taskade that you should try out:

Task list

Collaborators invitation feature (no organizational handle required)

Chat feature (with a call feature!)

Workspace feature (nothing new but...I'll get back to this later)

5 interchangeable neural-forest task list templates; List, Board, Action, Mindmap and Org Chart -- seamless with no error.

The capability to utilize this very platform as a presentation or exported into PDF task list printout.

Safe to say, Taskade buried me alive with the curation of beautiful images for the background; again...not relevant but needed to be said.

The Live Demosandbo lets you try it out for yourself although, at first glance, you may be wondering what on earth you are looking at. But it won't take long before you discover that it is quite intuitive.

Did I mention you can download and access it from just about ANYWHERE? Laptops, browser extensions and even smartphone apps. I'm not kidding when I said Taskade is multiplatform; they work on Windows, Mac, Android, iOS and Linux. Currently, I am testing it out using the Chrome extension and installed the app in my Android phone. It works like I expect it to so far.

What is the difference between the FREE and PAID version? 💰💰💰

As I just mentioned, you can sign-up for it for free and use it for life...for free. The priced version is seemingly there to accommodate the file size per upload you require; as of now. For free plan, you can upload 5MB file per upload while the paid version increases the size to 50MB per upload. Both versions offer:

Unlimited storage

Unlimited tasks entry

Unlimited project creation

Unlimited collaborators addition

The development team is currently adding more functionalities such as Project Activity Tracking, Integration to Dropbox, Google Drive and One Drive as well as Email Integration -- available for free.

Although it is mentioned that the free version of Taskade includes unlimited tasks, collaborators and all essential features, it was also mentioned that you will need to upgrade if you exceed the workspace limits which doesn't actually have any entailing elaborations which I will try to dig soon enough. But safe to say that if you are a single person using this tool, you are considered a team of 'one' where your shared projects in workspace to your 'editors' are still considered free. Only workspace the addition of workspace members are billed. This may imply that there are certain limits to how many individuals you can add into your workspace before you are required to upgrade. So far, visually, I see that the limit may be 2 people that makes up to 3 people per workspace (including yourself). You can find some details to pricing and FAQs here:

Taskade | Simple Pricing

Personally, I don't think USD5 is a hard bargain if you're self-employed and work with external parties collaboratively. If you're apart of an organization, feel free to ask for demo from them. Discount is possible if you're from a nonprofit or educational institution.

How I use Taskade? ☕

Well, given that it was free to sign-up, I tried it out straight away and I'm happy to report that I successfully managed to use it without having to google nor view any how-tos. That is a good thing! In fact, I am quite elated with just how easy it is to use this tool that I have used my personal email to help centralize and manage my work and personal work side-by-side. If you prefer some satellite view of your progress and all the task you need to complete to clear off certain objective, this is not a bad organization.

So I created 2 workspace: one for work and one for my personal tasks. Then I just collate all my tasks into monthly projects.

My personal tasks involve me updating my study progress and curating stuff I like online into my Tumblr blog.

Create studyblr workspace

Create new project in the studyblr workspace to organize and brainstorm Tumblr contents I plan to create and post: Tumblr: 2021/01.

Utilize the Mindmap template from all the options of templates shared and start creating the and organizing the content I want and tasks I need to execute to develop them.

Et voila! There all there is to it! It is easy peasy and you can start adding due dates as reminders and links as resources as well as hashtags for filtering in future. Check out some drafting I did so far in the screenshots below!

For more updates, check out their Updates page that fully utilizes Taskade to share all the updates straight from December 2017 till present and the chat function is there available for you to ask the Taskade team about the feature updates directly. Now that's awesome cause you know something's good if the one who makes them, actually uses them.😎😎😎

take care

Studying is hard enough when you are fighting the onset of hormonal hurricane of emotions while you're a teenager. Then you have you formative 5 to 6 years of collegiate years where you learn that your idealistic notions of the world is just plain snobbish and that you're one of the many that finds satisfaction in pushing your ideas into other people's head. Doing all that while studying, it was hard too.

Then comes the job hunting, climbing ladders to nowhere from one workplace to another...just drifting. That was the vacation off from studying and just wanting to find stability.

Then one day, you broke your heart at the same time you get an opportunity to a decent work somewhere. You ran. Then it was about understanding this whole new dimension of knowledge that you've fallen in love with. It was like your first love came back to find you and tell you he's back and that he won't leave you alone anymore. So, back to the books you fall into.

So yeah...studying is a rollercoaster of emotions. Learning is a lifelong journey. You're never too old to learn something new. And then phrase where you can't teach old dogs new tricks is just plain inaccurate. You can teach them new tricks and they can do it if they want to. It's the matter of either they want to do it or if their body can still keep up with them.

If you're an older student, I feel you. You feel left behind at times and frustrated because you feel like you can't catch up with things. If you're someone who's starting to work on research studies, it may be a harder state of mind. Because you're almost always on your own lamenting on you're comprehension of theories and questioning if you get whatever you absorbed right. So...it is hard. How do you know that you're alright and that you're not spinning down the road of doomed isolation? You don't. These are some of the glaring things I think are the universal problems among people who, with the courage of a lion, answered the call of hermitage and subject themselves to an occupation so feared that it is deemed over once high school ends; student:

Wardrobe reduction to daily uniform of hoodies/sweaters and jog-pants/sweatpants

It's totally ok. If you're wearing the same one everyday for the rest of the week, you still win. It's practical, it's easy and for hijabsters, the hoodie helps with instant full head cover while you run to receive those stuff you endlessly ordered online. There's nothing to be ashamed off.

💡I say: Shower 🚿. Every. Day. Twice a day is most ideal. Stay fresh and hygienic. If you're not going anywhere nor are you working out in those attire, then you're good. At least for a week. When you shower, you're giving your body a break from the exhausting task of slouching, the heat of your brain going overdrive and your own face breaking out from the stress. So yeah...shower. Wash your face. Brush your teeth. You're gonna be at risk of letting yourself go when you're left alone too comfortable in your own company. If you're an introvert, it feels like heaven but it doesn't mean you should be at the risk of losing out on the joys of prepping yourself to look good once in a while. Regularly make the effort to find decent clothes you'll use to go out on a Saturday window shopping and kick back to relax. On the rare occasion you get a break from your endless paper chasing, Zoom calls and writing, you can use your wardrobe clearing day to match few clothing and have a runway at home yourself or for a date with yourself to the Netflix movie you're gonna watch on your laptop. Who says you can't dress up to do online shopping? That's the only way you'll know that you do not need that new shade of Forencos lipstick you saw the other day. Duh.

Sudden weight gain/loss

I can't say that is unexpected especially if you're the kind who can go long without exercises and the type who munch while you work (which is a bad habit by the way). But sometimes you can't help if especially if you live on your own or have your own living space. Being on your own makes it kind of easy to get off-track about the norm of things; how much have you eaten today...is that your 5th coffee...should you be finishing that leftovers...etc. It is harder if you don't have your own kitchen and rely on packed food or processed ones.

💡I say: I can assure you, it is NOT unusual. This happens often. Each one of us have different eating habits. There isn't a flexible advise to cater this problem. But it helps to think that when you're setting up a study environment, you're setting up a living environment that enable you to be inspired enough for productivity. I make it a point to have food available but at a good distance and exercise attire/equipment nearby. Better yet, wear them. To curb that crazy cravings, I try my best to have my meal on-time; breakfast at 8 am, lunch at 12 pm or 1 pm etc. Eat what you love, but in moderation. Hydrate regularly. It's hard, I know. All the chips🍟 and chocolate chip cookies🍪 and sweetened 3-in-1 lattes☕...I just...well, just remember...in moderation and you're a human. Don't beat yourself up if you eat them anyway.

Back pain, knee pain, frozen shoulder...everything hurts

I have a hard time tearing away from what I am doing for the 20-minutes-work-5-minutes-rest rule but I try my best to maintain good posture. The bad habit of crouching and slouching at desk jobs is a universal problem. At the onset of the pandemic, for the first time in my life, my back felt strained. I panicked and started to seriously stretch myself and found that not only I am killing my back, I was not breathing properly when I am doing my work due to my posture.

💡I say: Don't break the bank trying to buy new furniture or tools because from experience, you end up not actually using them for the purpose you bought them in the first place. Eg. treadmill...you're more likely to hang your clothes or towels there...or super expensive yoga mats. Carpet works just fine too.

Standing desk is deemed to have little to no effects on spinal/muscle health by some studies but I went on ahead and made a make-shift standing desk. I found that I'm more alert when I work standing and breathe better. There was no contest...standing desk is a choice made. My standing table is an old dining table that I turned into my bed where I put my portable laptop desk. So, it also works as a barre that I used to stretch my legs for that mid-splits I've been working on.

These are some of the stuff that plague me daily and how I cope. How about you guys? How do you take care of yourself as someone who willingly serve yourself on a platter to tertiary educational torture to console your ever-thirsty curious mind?

survey123 offline

Survey123 for ArcGIS is perhaps, one of those applications that superficial nerds like me would like; it's easy to configure, kiddie-level degree of customization with 'coding' (for that fragile ego-stroke) and user-friendly template to use. 

No app development/coding experience is required to publish a survey form and believe it or not, you can, personalize your survey to not look so meh. 

It took me some time to stumble through the procedures of enabling this feature before I understand the 'ArcGIS Online' ecosystem to which this app is chained to. 

So how do we do it? And why doesn't it work pronto?

This issue may be due to the fact that when we first start creating our forms, we go through the generic step-by-step procedures that leave little to imagination what was happening. Most of the time, we're too eager to find out how it really work. 

When we publish a Survey123 form; be it from the Survey123 website portal or the Survey123 Connect for ArcGIS software, we are actually creating and publishing a folder that contains a hosted feature layer and a form. It is on that hosted feature layer that we add, delete, update or edit data it. From ArcGIS Online, it looks like any feature service that we publish out of ArcGIS Desktop or ArcGIS Pro, save for the special folder it is placed in with a 'Form' file. 

To enable any offline function in any hosted feature layer in ArcGIS Online, you will need to enable the 'Sync' feature. So far, in many technical articles that I have gone through to learn how to enable this offline feature always goes back to 'Prepare basemaps for offline use'. It is a tad bit frustrating. But my experience when deal with 'Collector for ArcGIS' gave me the sense of epiphany when it comes to Survey123. So when you have prepared your Survey123 form for offline usage and it still doesn't work...do not be alarmed and let's see how to rectify the issue. 

1. Locate your survey's hosted feature layer

At your ArcGIS Online home page, click 'Content' at the main tab. We're going to go directly to your hosted feature layer that was generated for your survey when you published. 

Locate your survey folder. Click it open 

In the survey folder, navigate to the survey's hosted feature layer and click 'Options' button; the triple ellipses icon

At at the dropdown, click 'View item details'. Please refer to the screenshot below: 

2. Change the hosted feature layer settings

At the item details page, navigate to the 'Settings' button at the main header and click it. This will prompt open the settings page for the feature layer. Refer to the screenshot below:

At the 'Settings' page, there are two tabs at the subheader; 'General' and 'Feature layer (hosted)'. Click 'Feature layer (hosted)' to configure its settings.

At the 'Feature layer (hosted)' option, locate the 'Editing' section. Here, check the 'Enable sync' option. This is the option that will enable offline data editing. Please refer to the following screenshot: 

Don't forget to click 'Save'

With this, your hosted feature layer which serves as the data model is enabled for synchronization. Synchronization helps to sync back any changes you've made when you're out on the field collecting data; editing, adding, deleting or update...depending on what feature editing you've configured. 

It's pretty easy once you get the hang of it and just bear in mind that the data hierarchy in the ArcGIS Online universe are as follows:

Feature layer (hosted) > Web map > Web application

Once you get that out of the way, go crazy with your data collection without any worries!