The Devil In The Details

Python: Geospatial Environment Setup (Part 1)

Here’s a quick run down of what you’re supposed to do to prepare yourself to use Python for data analysis.

Install Python ☑

Install Miniconda ☑

Install the basic Python libraries ☑

Create new environment for your workspace

Install geospatial Python libraries

🐍 Installing Python

Let’s cut to the chase. It’s December 14th, 2021. Python 3 is currently at 3.10.1 version. It’s a great milestone for Python 3 but there were heresay of issues concerning 3.10 when it comes to using it with conda. Since we’re using conda for our Python libraries and environment management, we stay safe by installing Python 3.9.5.

Download 👉🏻 Python 3.10.1 if you want to give a hand at some adventurous troubleshooting

Or download 👉🏻 Python 3.9.5 for something quite fuss-free

📌 During installation, don’t forget to ✔ the option Add Python 3.x to PATH. This enables you to access your Python from the command prompt.

Installing Miniconda

As a beginner, you’ll be informed that Anaconda is the easiest Python library manager GUI to implement conda and where it contains all the core and scientific libraries you ever need for your data analysis upon installation. So far, I believe it’s unnecessarily heavy, the GUI isn’t too friendly and I don’t use most of the pre-installed libraries. So after a few years in the darkness about it, I resorted to jump-ship and use the skimped version of conda; Miniconda.

Yes, it does come with the warning that you should have some sort of experience with Python to know what core libraries you need. And that’s the beauty of it. We’ll get to installing those libraries in the next section.

◾ If you’re skeptical about installing libraries from scratch, you can download 👉🏻 Anaconda Individual Edition directly and install it without issues; it takes some time to download due to the big file and a tad bit longer to install.

◾ Download 👉🏻 Miniconda if you’re up to the challenge.

📌 After you’ve installed Miniconda, you will find that it is installed under the Anaconda folder at your Windows Start. By this time, you will already have Python 3 and Anaconda ready in your computer. Next we’ll jump into installing the basic Python libraries necessary for core data analysis and create an environment to house the geospatial libraries.

📚 Installing core Python libraries

Core libraries for data analysis in Python are the followings:

🔺 numpy: a Python library that enables scientific computing by handling multidimensional array objects, or masked objects including matrices and all the mathematical processes involved.

🔺 pandas: enables the handling of ‘relational’ or 'labeled’ data structure in a flexible and intuitive manner. Basically enables the handling of data in a tabular structure similar to what we see in Excel.

🔺matplotlib: a robust library that helps with the visualization of data; static, animated or interactive. It’s a fun library to explore.

🔺 seaborn: another visualization library that is built based on matplotlib which is more high-level and produces more crowd-appealing visualization. Subject to preference though.

🔺 jupyter lab: a web-based user interface for Project Jupyter where you can work with documents, text editors, terminals and or Jupyter Notebooks. We are installing this library to tap into the notebook package that is available with this library installation

To start installing:

1️⃣ At Start, access the Anaconda folder > Select Anaconda Prompt (miniconda3)

2️⃣ An Anaconda Prompt window similar to Windows command prompt will open > Navigate to the folder you would like to keep your analytics workspace using the following common command prompt codes:

◽ To backtrack folder location 👇🏻

◽ Change the current drive, to x drive 👇🏻

◽ Navigate to certain folders of interest e.g deeper from Lea folder i.e Lea\folder_x\folder_y 👇🏻

3️⃣ Once navigated to the folder of choice, you can start installing all of the libraries in a single command as follows:

The command above will enable the simultaneous installation of all the essential Python libraries needed by any data scientists.

💀 Should there be any issues during the installation such as uncharacteristically long installation time; 1 hour is stretching it, press Ctrl + c to cancel any pending processes and proceed to retry by installing the library one by one i.e

Once you manage to go through the installation of the basic Python libraries above, you are half way there! With these packages, you are already set to actually make some pretty serious data analysis. The numpy, pandas and matplotlib libraries are the triple threat for exploratory data analysis (EDA) processes and the jupyter lab library provides the documentation sans coding notebook that is shareable and editable among team mates or colleagues.

Since we’re the folks who like to make ourselves miserable with the spatial details of our data, we will climb up another 2 hurdles to creating a geospatial workspace using conda and installing the libraries needed for geospatial EDA.

If you're issues following the steps here, check out the real-time demonstration of the installations at this link 👇🏻

See you guys in part 2 soon!

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?

Don't break the chain peeps! Reblog cause I'm looking for inspiration for my next masterpiece! 🙇🙇🙇

reblog/like if you’re an active studyblr/langblr

I’ve just unfollowed a bunch of inactive blogs, now that I follow ONLY 54 blogs??? pls reblog/like so I can have an active dashboard and new friends hehehe

Split by Attributes GP tool....when would you actually use this?

There are times when you're making a map but symbolizing using the symbology feature is not enough to characterize the data visually. Thus, having this tool makes cartographical work a little easier by generating copies of the original data, split into separate layers based on the attribute that we need. By doing this, it makes the task of adding the legend much easier in the layout as well.

Most often, when making maps for slide presentation, you would want to segregate data into separate layers with certain uniform values for a certain attribute and a create a new data layer which we can use over and over again.

Although definition query can help with visualizing and showing the features with the attribute value that we want, we may want to create a separate data to avoid compromising the original data or constantly repeating the task of typing/configuring the SQL commands.

This tool is valid for shapefiles and feature classes. Any other data types may need to be converted into those two formats before you can run it. Check out the long-winded demo below:

Since this tool is actually a Python script, it can be integrated into a code for batch geoprocessing or model for iteration over many data layers or interconnection to other tools; automation at its full-on glory! 😁

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.😎😎😎

Eyes on the Forest Sarawak | WWF-Malaysia

The ‘Eyes on the Forest’ Sarawak web application is developed with the joint effort of WWF-Malaysia and WWF-Japan. Emulating the successful ‘Eyes on the Forest’ Sumatra database, this web app intends to provide an undiluted information on the rich diversity of Sarawak’s unique wildlife, forests and land uses as well as increasing the transparency on the threats; deforestation, infrastructure developments and urbanization, as well as its drivers; concessions, agricultural activities and unsupervised resource harvesting.

Identifying where the threats, the drivers and the conservation targets are located will help in making a concrete point at the policy level and push for more boots on the ground to ensure that the protected areas stay protected. The baseline information provided are essential in the prompt intervention for biodiversity protection.

Data collected and consolidated from dispersed public sources and engineered for simple and direct visualization. Values are generated based on verified legislated information provided by stakeholders and state agencies to the Sarawak Conservation Programme (SCP) for WWF-Malaysia.

Developed and maintained by:

Azalea Kamellia

GIS Officer (SCP) | WWF- Malaysia

June 2018 - Present

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. 

mapshaper

Ok. 

I wanna know why have I never heard of this online tool before. Like, what the hell is wrong with the social media? Is something wrong with Twitter or Instagram or something that they never caught on mapshaper? Or was it just me and my hazardous ignorance, yet again?

Have you tried this free nifty online tool that literally simplify crazy complicated shapefile polygons like it’s no one’s business?!

It started with some last minute inspiration on how to collate data from 3 different regions; developed from remote sensing techniques which vary from one another. The common output here is to turn all of them into a vector file; namely shapefile, and start working on the attribute to ease merging of the different shapefile layers.

Once merged, this shapefile is to be published as a hosted feature layer into the ArcGIS Online platform and incorporated into a webmap that serves as a reference data to configure/design a dashboard. What is a dashboard? It's basically an app template in ArcGIS Online that summarizes all the important information in your spatial data. It's a fun app to create, no coding skills required. Check out the gallery here for reference:

Operations Dashboard for ArcGIS Gallery

There are two common ways to publish hosted feature layer into ArcGIS Online platform.

Method 1: Zip up the shapefile and upload it as your content. This will trigger the command inquiring if you would like to publish it as a hosted feature layer. You click 'Yes' and give it a name and et voila! You have successfully publish a hosted feature layer.

Method 2: From an ArcGIS Desktop or ArcGIS Pro, you publish them as feature service (as ArcMap calls them) or web layer (as the its sister ArcGIS Pro calls them). Fill up the details and enabling the function then hit 'Publish' and it will be in the platform should there be no error or conflicting issues.

So, what was the deal with me and mapshaper? 

🛑 A fair warning here and please read these bullet points very carefully:

I need you to remember...I absolve any responsibility of what happens to your data should you misinterpreted the steps I shared. 

Please always  👏🏻  BACK 👏🏻 UP  👏🏻  YOUR 👏🏻 DATA. Don’t even try attempting any tools or procedure that I am sharing without doing so. Please. Cause I am an analyst too and hearing someone else forget to save their data or create a backup is enough to make me die a little inside. 

For this tool, please export out the attribute table of your shapefile because this tool will CHANGE YOUR SHAPEFILE ATTRIBUTES. 

When I was publishing the vector I have cleaned and feature-engineered via ArcGIS Pro...it took so long that I was literally dying inside. I'm not talking about 20 minutes or an hour. It took more than 12 hours and it did not conjure the 'Successfully published' notification as I would've expected from it.

So at around 5.30 am, I randomly type 'simplify shapefily online free'. Lo and behold, there was mapshaper.

All I did was, zip up my polygon, drag it to the homepage and it will bring you to the option of choosing the actions that will be executed while the data is being imported into mapshaper:

detect line intersections

snap vertices

This option will help you to detect the intersections of lines within your vector/shapefile. This can help identify topological error.

The option to snap vertices will snap together points of similar or almost identical coordinate system. But it does not work with TopoJSON formats.

There is something interesting about this options too; you can enter other types of customized options provided by the tool from its command line interface! But hold your horses peeps. I did not explore that because here, we want to fix an issue and we'll focus on that first. I checked both options and import them in.

This will bring the to a page where there you can start configuring options and method to simplify your vector.

To simplify your shapefile, you can have both options to prevent the shape of the polygon being compromised; prevent shape removal, and to utilize the planar Cartesian geometry instead of the usual geoid longitude and latitude; use planar geometry. The implication of the second option is not obvious to me yet since all I wanted was to get the data simplified for easy upload and clean topology, thus, I chose both options to maintain the shape and visibility of all my features despite the highest degree of simplification.

Alike to the options of methodology for simplication in the mainstream software, I can see familiar names:

Douglas-Peuker

Visvalingam / effective area

Visvalingam / weighted area

First and foremost, I had no slightest idea of what these were. Like for real. I used to just go first for the default to understand what sort of output it will bring me. But here, the default; Visvalingam / weighted area, seemed like the best option. What are these methodologies of simplification? There are just algorithms used to help simplify your vectors:

🎯 Douglas-Peucker algorithm decimates a curve composed of line segments to a similar curve with fewer points (Ramer-Douglas-Peucker algorithm, Wikipedia; 2021).

🎯 Visvalingam algorithm is a line simplication operator that works eliminating any less significant points of the line based on effective area concept. That basically means that the triangle formed by each of the line points with two of its immediate neighboring points (Visvalingam Algorithm | aplitop).

🎯 Visvalingam algorithm with weight area is another version of Visvalingam algorithm of subsequent development where an alternative metrics is used and weighted to take into account the shape (Visvalingam & Whelan, 2016).

For reasons I can't even explain, I configured my methodology to utilize the third option and now that I have the time to google it, Thank God I did.

Then, see and play with the magic at the 'Settings' slider where you can adjust and view the simplification made onto the vector! I adjusted it to 5%. The shape retained beautifully. And please bear in mind, this vector was converted from a raster. So, what I really wanted is the simplified version of the cleaned data and to have them uploaded.

Now that you've simplified it, export it into a zipped folder of shapefile and you can use it like any other shapefile after you extracted it.

Remember when I say you have got to export your table of attributes out before you use this tool? Yea...that's the thing. The attribute table will shock you cause it'll be empty. Literally. With only the OBJECTID left. Now, with that attribute table you've backed up, use the 'Join Table' tool in ArcGIS Pro or ArcMap and join the attribute table in without any issues.

Phewh!!

I know that it has alot more functions than this but hey, I'm just getting started. Have you ever done anything more rocket science than I did like 2 days ago, please share it with the rest of us. Cause I gotta say, this thing is cray!! Love it so much.

mapshaper developer, if you're seeing this, I 🤟🏻 you!

UPDATE

I have been asked about the confidentiality of the data. I think this is where you understand the reason behind the fact that they will work even with using just the ‘.shp’ file of the shapefile since _that_ is the vector portion of the shapefile. 

Shapefile is a spatial data format that is actually made up of 4 files; minimum. Each of these files share the same name with different extensions; .prj, .shx, .shp and .dbf. Although I am not familiar with what .shx actually accounts for, the rest of them are pretty straightforward:

.prj: stores the projection information

.dbf: stores the tabulated attributes of each features in the vector file

.shp: stores the shape/vector information of the shapefile. 

So, as the tool indicate, it actually helps with the vector aspect of your data which is crucial in cartography. 

33rd National Geoscience Conference 2021 (NGC 2021)

Tool: ArcGIS Pro, ArcGIS Pro Deep Learning extension, Python, Jupyter Notebook Technique: Deep learning; semantic segmentation, cartography, remote sensing

The presentation of abstract outlining the implementation of deep learning in land cover classification across the Borneo island. It uses the Sentinel-2 image data and the band combination that differentiates the bareland, tree cover as well as waterbodies and croplands whilst training the U-Net model using the referenced data collected.

Please find the abstract published here:

Warta Geologi, Vol. 47, No. 1, April 2021

The presentation slide can be accessed at the following link 👇🏻:

Malaysia Forest Cover 2020 | WWF-Malaysia

Tool: ArcGIS Pro 2.9.3, Operations Dashboard ArcGIS & ArcGIS Online Technique: Data transformation and geometric calculation

WWF-Malaysia Forest Cover Baseline is a dashboard of forest cover extent status in selected land uses across Malaysia's region, methodology of analysis and resources involved in the exercise.

The WWF-Malaysia Forest Cover Baseline and Forest Cover Key Performance Index (KPI) is a task undertaken by the Conservation Geographical Information System (CGIS) Unit to amass the discrete information of forest cover extent across Malaysia's 3 main region of legislation: Peninsular Malaysia, Sarawak and Sabah. This exercise produces a concise dashboard report in an online platform that describes the processed information on the forest cover status as well as their prospective areas identified for conservation work.

Report can be interactively accessed at the following:

The dashboard can be accessed at Malaysia Forest Cover 2020.

📌 Availability: Retracted in 2021