diff --git a/.github/workflows/ci-checks.yml b/.github/workflows/ci-checks.yml index 488e98dca..24f766d5c 100644 --- a/.github/workflows/ci-checks.yml +++ b/.github/workflows/ci-checks.yml @@ -18,6 +18,8 @@ jobs: files: . config_file: .markdownlint.yml + + py_formatting: runs-on: ubuntu-latest steps: diff --git a/.vscode/settings.json b/.vscode/settings.json index 252022b48..3fc9a4fe1 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -122,5 +122,6 @@ "source.fixAll.ruff": "explicit", "source.organizeImports.ruff": "explicit" } - } + }, + "cSpell.words": ["NFDB"] } diff --git a/.vscode/spellright.dict b/.vscode/spellright.dict new file mode 100644 index 000000000..8e1581878 --- /dev/null +++ b/.vscode/spellright.dict @@ -0,0 +1,5 @@ +shx +prj +Jupyter +shapefile +shp diff --git a/0_domain_study/README.md b/0_domain_study/README.md index 308b71113..b8f638aba 100644 --- a/0_domain_study/README.md +++ b/0_domain_study/README.md @@ -1 +1,147 @@ # Domain Research + +## Research Question Table + +### Research Question 1 (Alona) + +**Research Question:** +How are the frequency and size of wildfires in North America related +to health problems caused by air pollution? + +**Research Novelty:** +Not really new + + + +**Expected Data Availability:** +Quite available + +**Problems:** +Although there is a lot of data, the topic is not really new and +doesn't seem very promising + +**Sources or Brief Explanation:** +Studies on PM2.5 in the US + + + + +--- + +### Research Question 2 (Alona) + +**Research Question:** +How are income level and the source of antibiotic prescriptions +related in Ukraine? + +**Research Novelty:** +Seems to be quite new + + + +**Expected Data Availability:** +We might get some data from government statistics or surveys, +but haven't checked yet + +**Problems:** +Prescription and purchase data may be incomplete or unofficial + +**Sources or Brief Explanation:** +WHO and UNICEF reports + +--- + +### Research Question 3 (Alona) + +**Research Question:** +How does the intensity of shelling in residential areas of Ukraine +affect access to and quality of online education? + +**Research Novelty:** +Very high + +**Expected Data Availability:** +Damage data: +[ACLED report on Russian targeting in Ukraine](https://acleddata.com/2025/02/21/bombing-into-submission-russian-targeting-of-civilians-and-infrastructure-in-ukraine/) + +Education data: Kolibri, Coursera for Refugees, UNICEF + +**Problems:** +Educational data is tricky to get. We should ask some big platforms +and wait a long time. They don’t usually specify regions in Ukraine. + +**Sources or Brief Explanation:** +UNICEF and UN reports + +--- + +### Research Question 4 (Alona) + +**Research Question:** +How does the availability of a well-developed public transportation +system influence processed food consumption in car-free households in Canada? + +**Research Novelty:** +High – haven’t found an exact match in literature + +**Expected Data Availability:** +Not sure + +**Problems:** +Very area-specific. Requires filtering by income level, car ownership, +and food type + +**Sources or Brief Explanation:** +_(Not specified)_ + +--- + +### Research Question 5 (Alona) + +**Research Question:** +How does non-prescription antibiotic use affect the spread of +antibiotic-resistant infections in Ukraine? + +**Research Novelty:** +Haven’t seen studies on this for Ukraine + +**Expected Data Availability:** +Some lab data from universities or public health sources. +Survey/pharmacy data limited + +**Problems:** +Black market access to antibiotics; unclear where we can +get microbiological data + +**Sources or Brief Explanation:** +WHO AMR reports + +### Research Question 6 (Zaid) + +**Research Question:** +How effective is Satellite Image Analysis at Predicting Deforestation in Malaysia? + +**Research Novelty:** +High – not much research on this topic in Malaysia. +Overall, satellite image analysis is very well-studied, but in the context +of Predicting deforestation, we could only find very few papers. +When it comes to predicting deforestation in Malaysia, we found no papers. + +**Expected Data Availability:** +Highly available. +Sattelite images are available from many sources, and we are using the +google earth engine to access them. +The vegetation index data is also available from Global Forest Watch. +Other data such as deforestation rates and forest cover are easily +accessible from government and environmental organizations. + +**Problems:** +Satellite image analysis can be computationally intensive. +Satellite images are HUGE. They requires lots of storage and time to work with. + +**Sources or Brief Explanation:** + +- [Global Forest Watch](https://www.globalforestwatch.org/) +- [Google Earth Engine](https://earthengine.google.com/) +- We hope to use the vegetation index and satellite images to train a model + to predict deforestation in Malaysia. diff --git a/0_domain_study/guide.md b/0_domain_study/guide.md index d36e40c63..f53dec71e 100644 --- a/0_domain_study/guide.md +++ b/0_domain_study/guide.md @@ -1,15 +1,69 @@ # Domain Study: Guide -To do meaningful research in a domain, you need to learn what others already do -and don't understand in this area. Use this folder to organize your group's -understanding of your research domain including: your own summaries, helpful -PDFs, links you found helpful, ... +To do meaningful research, you must know what others do and don’t understand. +Use this folder to collect your group’s knowledge of your research domain. +Include your own summaries, PDFs, and useful links. -This folder is different from `/notes` because it contains _only_ information -about your research domain. When deciding what goes here, ask yourself this -question: _Would someone need to know this to understand our research?_ +This folder is not like `/notes` — it contains _only_ research domain info. +Ask yourself: _Would someone need this to understand our research?_ ## README.md -Use this folder's README to document all the notes and resources in this folder. -Someone shouldn't need to read through _everything_ to find what they need. +Use this folder’s README to describe the notes and files inside. +Someone should not need to read everything to find key info. + +## Chosen Question + +How effective is Satellite Image Analysis at Predicting Deforestation +in Malaysia? + +### Why this question? + +Malaysia has vast forests, but deforestation is a serious issue. +Global Forest Watch shows a 31% drop in tree cover since 2000. +It is important to track and predict deforestation early. +If satellite image analysis works, it can support conservation. +It could also be a low-cost tool for environmental protection. + +### Satellite Image Analysis + +This means using satellite images to study Earth’s surface. +We can analyze land use, vegetation, and environmental changes. + +Image resolution matters. High-res images give better results +but need more storage and processing time. + +We plan to use free Landsat images from Google Earth Engine. +They have 30m resolution and are updated every 16 days. +This offers a balance between quality and efficiency. + +There are 3m daily images from PlanetScope, but they are costly. +They also need too many resources for our timeframe. +They may help future studies track trees at an individual level. + +### Rough Plan + +- **Data Collection**: + - Get satellite images and vegetation data from GFW and Earth Engine. + - GFW makes it easy to find vegetation index data. + - Google Earth Engine provides free satellite images. + We need to create accounts and request API access. + We also need to write code to extract and process images. + - Gather other data from public sources and institutions. + +- **Model Training**: + - Use k-means clustering with 5 time-based clusters. + - Combine vegetation index and image data to detect forest loss. + - Add more features as the project progresses. + +- **Model Evaluation**: + - Check how well the model predicts real deforestation. + - Compare predicted and actual results to assess performance. + +### Resources + +- [Global Forest Watch](https://www.globalforestwatch.org/) +- [Google Earth Engine](https://earthengine.google.com/) +- [Google Earth Engine API Docs](https://developers.google.com/earth-engine) +- [Interesting Paper](https://arxiv.org/pdf/1803.02489) +- More resources will be added as we find them. diff --git a/0_domain_study/related_research_topics/forests.md b/0_domain_study/related_research_topics/forests.md new file mode 100644 index 000000000..d40f501d8 --- /dev/null +++ b/0_domain_study/related_research_topics/forests.md @@ -0,0 +1,102 @@ +# Forests + +- Earth surface is divided into large geographic areas called **Biomes**. + +- Each biome is characterized by distinct climate, vegetation, and animal life. + +![alt text](image.png) + +![alt text](image_1.png) + +- **Forests** are a biome where treas are the dominant life-form. + +- There are three types of forests: + +1. **Boreal forests:** also known as taiga, + are found in the subarctic regions and are + characterized by cold temperatures and coniferous trees. + +![alt text](image_2.png) + +2.**Temperate forests:** located in mid-latitudes, experience four distinct +seasons and can be either deciduous (trees that lose their leaves seasonally) or +coniferous. + +![alt text](image_3.png) + +3.**Tropical forests:** near the equator, + are known for their warm temperatures, high + rainfall, and exceptional biodiversity. + +![alt text](image_4.png) + +- Forests can be **dry** or **humid** +- Forests can be: + +1. **Primary** or old growth: + +- are those that have not been significantly disturbed by human activity. + +2.**Secondary**: + +- are areas where forests have regrown + after being cleared or disturbed by human activities or natural events. + +![alt text](image_6.png) + +## Some relevant terms + +**Tree cover:** + +- Encompasses all vegetation taller than 5 +meters, including natural forests and tree crops (like rubber, oil palm, etc.). +- May be expressed as a percentage of the area covered by tree canopies, or in +absolute terms (e.g., square kilometers). + +**Tree canopy:** + +- Refers to the layer of branches and leaves formed by trees, effectively +creating a "roof" over the ground. + +**Tree canopy density, canopy cover or crown cover**: + +- is the proportion of ground area covered +by this tree canopy, usually expressed as a percentage. +- It essentially measures how much of the +ground is shaded or covered by tree foliage when viewed from above. + +![alt text](image_7.png) + +**Tree cover loss:** + +- removal or mortality of that tree cover, regardless of the cause. +Can be : + +1. human caused: eg. Deforestation. +2. due to natural causes: eg. Wildfires + +**Some measurement units:** + +- Hectare(ha) : 10,000 square meters. +- Kha : Kilo hectares. +- Mha : million hectares. +- Gha : Global hectares. + +- A global hectare represents the biologically productive area (cropland, +grazing land, forest, fishing grounds, and built-up land) needed to provide the +resources consumed and absorb the waste generated by a population, but with the +productivity of each land type adjusted to the world average for that year. +- **Ecological Footprint:** +Global hectares are the primary unit used to express an ecological footprint, which +is a measure of human demand on the Earth's ecosystems. +- **Example:** +If a country's ecological footprint is 4.5 +gha per person, it means, on average, that +each person in that country requires the +equivalent of 4.5 hectares of biologically +productive land and water, with the average +world productivity, to provide for their resource needs and waste absorption. + +![alt text](image_8.png) + +## Forests in Canada diff --git a/0_domain_study/related_research_topics/image.png b/0_domain_study/related_research_topics/image.png new file mode 100644 index 000000000..6700dcf3f Binary files /dev/null and b/0_domain_study/related_research_topics/image.png differ diff --git a/0_domain_study/related_research_topics/image_1.png b/0_domain_study/related_research_topics/image_1.png new file mode 100644 index 000000000..db0fd3c50 Binary files /dev/null and b/0_domain_study/related_research_topics/image_1.png differ diff --git a/0_domain_study/related_research_topics/image_2.png b/0_domain_study/related_research_topics/image_2.png new file mode 100644 index 000000000..b357c3299 Binary files /dev/null and b/0_domain_study/related_research_topics/image_2.png differ diff --git a/0_domain_study/related_research_topics/image_3.png b/0_domain_study/related_research_topics/image_3.png new file mode 100644 index 000000000..42defce71 Binary files /dev/null and b/0_domain_study/related_research_topics/image_3.png differ diff --git a/0_domain_study/related_research_topics/image_4.png b/0_domain_study/related_research_topics/image_4.png new file mode 100644 index 000000000..eb38a5a6c Binary files /dev/null and b/0_domain_study/related_research_topics/image_4.png differ diff --git a/0_domain_study/related_research_topics/image_5.png b/0_domain_study/related_research_topics/image_5.png new file mode 100644 index 000000000..81eb6f664 Binary files /dev/null and b/0_domain_study/related_research_topics/image_5.png differ diff --git a/0_domain_study/related_research_topics/image_6.png b/0_domain_study/related_research_topics/image_6.png new file mode 100644 index 000000000..6d1de46dd Binary files /dev/null and b/0_domain_study/related_research_topics/image_6.png differ diff --git a/0_domain_study/related_research_topics/image_7.png b/0_domain_study/related_research_topics/image_7.png new file mode 100644 index 000000000..c5f9b704e Binary files /dev/null and b/0_domain_study/related_research_topics/image_7.png differ diff --git a/0_domain_study/related_research_topics/image_8.png b/0_domain_study/related_research_topics/image_8.png new file mode 100644 index 000000000..e139d6bbb Binary files /dev/null and b/0_domain_study/related_research_topics/image_8.png differ diff --git a/0_domain_study/related_research_topics/prescribed_fires.md b/0_domain_study/related_research_topics/prescribed_fires.md new file mode 100644 index 000000000..d3e767bae --- /dev/null +++ b/0_domain_study/related_research_topics/prescribed_fires.md @@ -0,0 +1,132 @@ +# Prescribed Fires + +- Also known as controlled burn or prescribed burn, is the planned and +managed application of fire to a +specific land area to achieve predetermined ecological or land +management objectives, AKA , a healthy +dose of fire. + +- Cultural burning is a traditional land management practice used by +Indigenous peoples worldwide for millennia. + +- Because of the lack of understanding of fire importance to increase the +reselience of ecosystems, cultural +fires were suppressed and banned. + +- [A healthy dose of fire: prescribed fires at Parks Canada](https://parks.canada.ca/nature/science/especes-species/feu-fire) +explains how +prescribed fires are not only preventive, reducing the risk of +wildfires, but is also a naturally +regenerative process and can provide a fresh start for an ecosystem, it allows + sunlight and greater airflow for different trees to thrive, remove some + of the competitive trees, it also decreases fungal disease occurence, + and increase the population of some animals. + +- 40 years ago, Parks Canada learned from the negative outcomes of the + previous conservation approach of suppressing fire shifted the + conservation approach to using prescribed fire to re-introduce fire + to the landscape in a controlled manner. + +## Before starting a prescribed fire + +1. Ecosystem Assessment: + is the ecosystem fire-dependent(meaning they require fire to meet + the needs of their inhabitants and preserve biodiversity), fire-sensitive + (vulnerable to fire), or fire-independent(not significantly impacted by fire). + +2. Objectives: + is it to reduce wildfires, habitat mangement, etc... + +3. Site selection criteria: + + - Weather conditions: such as temperature, wind speed and direction. + - Topography: eg. slope of the area. + - Smoke management: land managers and air regulators work to choose a + suitable day, under favorable atmospheric conditions, to allow + smoke to disburse and dissipate, to reduce impact on nearby communities. + +4. Most prescribed fires are planned in spring and spring to prevent major + fires in warmer dryer seasons. + +5. [Ignition plan](https://extension.oregonstate.edu/catalog/pub/em-9387-prescribed-fire-basics-ignition-techniques-tools), + including tools and fuel used and fire spread pattern. + +## Prescribed Fires to Prevent Wildfires + +- Wildfires are particularly common in regions + with dry climates and abundant fuel sources. + +- Fuel sources are unchecked vegetation buildup +including dry grass, dead plants, and other +flammable materials, and fuel ladder which are + small trees that help fire reach tree canopies. + +- lightening or man-made fires then cause +wildfires in the presence of these fuel sources. + +[Prescribed Fire Basics](https://extension.oregonstate.edu/collection/prescribed-fire-basics) + is a collection of articles dicussing different aspects of prescribed fires. + +## Fire regime + +- Fire regime describes the pattern of wildland fire in a particular area or +ecosystem over time. It is influenced by: +fuel, climate, ignition source, topography, land use, fire suppression activities + +The pattern include: +Type: + +1. Ground fire: burning organic materials at varying depth beneath the forest floor. +2. Surface fire: burns through ground-level +materials like dead leaves and vegetation without reaching the tree crowns. +3. Crown fire: Burn tree canopies along with surface fire creating wall of flame. + +![alt text](image_5.png) + +Frequency: + + - number of fires per year, or fire interval which is number of years + between 2 fires. + +Intensity: + +- [Fire behavior](https://natural-resources.canada.ca/forest-forestry/wildland-fires/fire-behaviour) + +Size: +area burned in hectares, a large fire is > 200 ha + +Seasonality: + +- Seasonal changes influence fuel and weather conditions, and determine leaf +flush the production of new leafs. + +Severity: + +Cause of ignition: + + 1. Natural(lightening) + 2. Human activity(campfires) + +## Fire Regime Zonation Systems In Canada + +- A fire regime zonation system divides + landscapes into distinct geographical areas that share similar fire behaviours + and environmental characteristics. + +1. Fire Regime Units (FRUs): + + - 60 geographical areas across Canada + +2. Fire Regime Types (FRTs): + + - 15 classifications across Canada + +[stocks et al. 2002](https://cdnsciencepub.com/doi/10.1139/cjfr-2018-0293#refg56) + +[Natural resources Canada](https://cdnsciencepub.com/doi/10.1139/cjfr-2018-0293#refg41) + +[Canadian National Fire Database (CNFDB)](https://cwfis.cfs.nrcan.gc.ca/ha/nfdb) + +[Fire-regime changes in Canada over the last half century](https://cdnsciencepub.com/doi/10.1139/cjfr-2018-0293#refg9) + +[Canada’s National Forestry Database](http://nfdp.ccfm.org/en/index.php) diff --git a/0_domain_study/related_research_topics/satellite_images.md b/0_domain_study/related_research_topics/satellite_images.md new file mode 100644 index 000000000..be65ddcfb --- /dev/null +++ b/0_domain_study/related_research_topics/satellite_images.md @@ -0,0 +1,43 @@ +# Satellite Imaging + +- The vastness of global forests poses a challenge for monitoring on the ground. +- satellite technology offer a comprehensive, timely, and efficient means +to keep tabs forest cover changes. +- There are several types of satellite sensors that are used for detecting deforestation: + +1. **Optical sensors:** +These capture images in visible light, much +like a standard camera, but can also detect +non-visible wavelengths, enabling them to +monitor vegetation health and moisture content. +2. **Radar sensors:** +Using radio waves, radar sensors can penetrate clouds and even capture data at +night. They're particularly useful in regions with frequent cloud cover or in +assessing structural characteristics of forests. +3. **Thermal sensors:** +Detecting radiation in the infrared spectrum, these sensors are instrumental in +identifying forest fires and areas of heat stress in forests. + +- **Time-series data:** +Sequences of images over time facilitates tracking of gradual changes in forest cover +and helps distinguish between temporary shifts (like seasonal changes) and +permanent ones (such as deforestation). + +## Techniques and Analysis + +1. **Spectral analysis:** +Examining the different wavelengths of satellite sensors to identify specific +materials on the ground. For example, healthy vegetation reflects light +differently from stressed or dead vegetation. By analyzing these spectral +signatures, scientists can assess forest health and detect early signs of degradation. + +2. **Machine learning and AI :** +Algorithms can be trained to recognize patterns associated with deforestation, +such as the layout of roads leading to logging areas or the distinctive shapes of +clear-cuts. + +3. **Data fusion:** +integrating satellite imagery with ground-based observations. + +[This article](https://up42.com/blog/track-forest-fires-satellite-imagery-normalized-burn-ratio) +explain how satellite images are used in to monitor fires at different stages. diff --git a/1_datasets/README.md b/1_datasets/README.md index 157ea3aad..3cdca8083 100644 --- a/1_datasets/README.md +++ b/1_datasets/README.md @@ -1 +1,46 @@ -# Datasets +# Wildfire & Prescribed Burn Datasets + +This directory contains all data sources collected and used for **Milestone 2** +of our wildfire risk mitigation project. +Our main research goal is to use satellite imagery and historical fire records +to support **prescribed burn planning** in Canada. + +We aim to understand where wildfires have occurred, how prescribed burns are +distributed, and what data can support modeling future fire risks. + +--- + +## Contents + +### National_Fire_Database + +Point-based wildfire dataset from the Canadian National Fire Database (NFDB). +This includes: + +- Individual fire records with attributes such as date, location, cause, + response type, and area burned +- Ability to identify prescribed burns using `CAUSE == 'H-PB'` +- A Jupyter Notebook to explore, filter, and analyze fires + +--- + +## How to Use These Datasets + +### Explore Point Fires (`National_Fire_Database/`) + +Navigate to the `National_Fire_Database/` folder and open the included Jupyter notebook. + +The notebook demonstrates how to: + +- Display the first 50 fire records +- Filter for prescribed burns (e.g., `CAUSE == 'H-PB'`) +- Explore useful metadata fields (cause, agency, location, dates, etc.) +- Count and compare fire types + +--- + +## Cleaning and Reproducibility Notes + +- All scripts are designed to work with data downloaded from official sources +- Raw data files are not included in this repo due to size limits +- Instructions are provided in subdirectories for downloading and placing raw data diff --git a/1_datasets/national_fire_database/README.md b/1_datasets/national_fire_database/README.md new file mode 100644 index 000000000..423ee9b87 --- /dev/null +++ b/1_datasets/national_fire_database/README.md @@ -0,0 +1,45 @@ +# National Fire Database (NFDB) - Point Data + +This folder contains a Jupyter notebook to explore historical wildfire records + from the **Canadian National Fire Database (NFDB)**. + +We use this data to analyze wildfire locations, causes, response types, + and identify **prescribed burns** (controlled fires used to reduce risk). + +--- + +## Required Data + +Due to file size, the raw shapefile is **not included** in this repository. + +To run the notebook: + +1. Download the official NFDB Point shapefile (.zip) from: + 🔗 [Download Link – NFDB_point_20250519.zip](https://www.dropbox.com/scl/fi/v1as8zlybx1fc4zzk71xm/NFDB_point.zip?rlkey=zqquce868aawnmqy9xhcmnsqg&st=c3gqm0s7&dl=0) + +2. Unzip it in this directory. The folder should contain files like: +NFDB_point_20250519.shp +NFDB_point_20250519.dbf +NFDB_point_20250519.shx +NFDB_point_20250519.prj + +--- + +## What This Notebook Does + +- Displays the first 50 fire records with selected metadata +- Filters fires to find those with `CAUSE == 'H-PB'` (prescribed burns) + +--- + +## Cleaning Notes + +- Some records may have incomplete dates (DAY = 1, etc.) +- Non-wildfire incidents and missing location data may need to be filtered + +--- + +## Files in This Folder + +- `explore_NFDB.ipynb` – interactive notebook for data exploration +- `README.md` – this documentation file diff --git a/1_datasets/national_fire_database/read_nfdb.ipynb b/1_datasets/national_fire_database/read_nfdb.ipynb new file mode 100644 index 000000000..2a4b891f2 --- /dev/null +++ b/1_datasets/national_fire_database/read_nfdb.ipynb @@ -0,0 +1,1436 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "4bafc962", + "metadata": {}, + "source": [ + "# 🔽 Setup Instructions\n", + "\n", + "This notebook requires the NFDB Point Dataset, which is too large to host on GitHub.\n", + "\n", + "To use this notebook:\n", + "\n", + "1. Download the dataset from [Google Drive](https://your-download-link.com).\n", + "2. Unzip the file into the same directory as this notebook.\n", + " It should contain files like `NFDB_point_20250519.shp`, `.shx`, `.dbf`, etc.\n", + "3. Run the cells below to explore and filter fire data.\n", + "\n", + "Note: This notebook was tested with the version dated **May 2025 (NFDB_point_20250519)**.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "3923d887", + "metadata": {}, + "outputs": [], + "source": [ + "import geopandas as gpd\n", + "import os\n", + "\n", + "# Check if shapefile exists\n", + "shapefile = \"NFDB_point_20250519.shp\"\n", + "if not os.path.exists(shapefile):\n", + " raise FileNotFoundError(\n", + " f\"{shapefile} not found. Please follow setup instructions above.\"\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "6fcce082", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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32AB-2024-CWF-003-2024ABNoneNone20242222024-02-22NaTNaT0.10HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1378893.055 448845.726 0)
33AB-2024-PWF-003-2024ABNoneNone2024352024-03-05NaTNaT0.10HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1302860.745 1011527.785 0)
34AB-2024-PWF-004-2024ABNoneNone2024352024-03-05NaTNaT0.80HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1305953.361 1009063.084 0)
35AB-2024-PWF-002-2024ABNoneNone20242202024-02-20NaTNaT0.04HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1316353.752 1014522.535 0)
36AB-2024-LWF-007-2024ABNoneNone2024382024-03-08NaTNaT0.10HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1088892.243 804111.541 0)
37AB-2024-SWF-007-2024ABNoneNone2024352024-03-05NaTNaT0.02HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1221168.565 888872.073 0)
38AB-2024-LWF-008-2024ABNoneNone2024382024-03-08NaTNaT0.01HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-965480.692 725071.516 0)
39AB-2024-RWF-002-2024ABNoneNone20243112024-03-11NaTNaT0.20HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1352491.23 606371.113 0)
40AB-2024-HWF-002-2024ABNoneNone20243122024-03-12NaTNaT0.01HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1262695.951 1277707.595 0)
41AB-2024-PWF-005-2024ABNoneNone20243122024-03-12NaTNaT1.31HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1406771.122 1089375.802 0)
42AB-2024-LWF-009-2024ABNoneNone20243132024-03-13NaTNaT0.10HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-951370.69 883143.638 0)
43AB-2024-PWF-006-2024ABNoneNone20243142024-03-14NaTNaT0.01HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1322677.547 1101879.136 0)
44AB-2024-EWF-006-2024ABNoneNone2024342024-03-04NaTNaT0.01HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1368206.328 743441.56 0)
45AB-2024-SWF-009-2024ABNoneNone20243172024-03-17NaTNaT0.06HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1246445.666 889134.341 0)
46AB-2024-GWF-007-2024ABNoneNone20243152024-03-15NaTNaT0.90HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1358677.001 892209.033 0)
47AB-2024-PWF-007-2024ABNoneNone20243182024-03-18NaTNaT0.20HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1379949.504 1055572.462 0)
48AB-2024-LWF-013-2024ABNoneNone20243192024-03-19NaTNaT0.01HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1011996.534 745868.235 0)
49AB-2024-SWF-010-2024ABNoneNone20243192024-03-19NaTNaT0.10HHNoneNone2025-04-07AB_NFDB_2024NonePOINT Z (-1133745.417 933310.31 0)
\n", + "
" + ], + "text/plain": [ + " NFDBFIREID SRC_AGENCY NAT_PARK FIRENAME YEAR MONTH DAY \\\n", + "0 AB-2024-CWF-001-2024 AB None None 2024 1 2 \n", + "1 AB-2024-HWF-001-2024 AB None None 2024 1 5 \n", + "2 AB-2024-SWF-001-2024 AB None None 2024 1 17 \n", + "3 AB-2024-LWF-001-2024 AB None None 2024 1 9 \n", + "4 AB-2024-LWF-002-2024 AB None None 2024 1 9 \n", + "5 AB-2024-PWF-001-2024 AB None None 2024 1 26 \n", + "6 AB-2024-EWF-001-2024 AB None None 2024 1 30 \n", + "7 AB-2024-MMD-001-2024 AB None None 2024 1 29 \n", + "8 AB-2024-MMD-002-2024 AB None None 2024 1 29 \n", + "9 AB-2024-LWF-003-2024 AB None None 2024 1 15 \n", + "10 AB-2024-RWF-001-2024 AB None None 2024 1 31 \n", + "11 AB-2024-WWF-001-2024 AB None None 2024 2 1 \n", + "12 AB-2024-GWF-001-2024 AB None None 2024 1 8 \n", + "13 AB-2024-EWF-002-2024 AB None None 2024 2 6 \n", + "14 AB-2024-MWF-001-2024 AB None None 2024 1 21 \n", + "15 AB-2024-CWF-002-2024 AB None None 2024 1 30 \n", + "16 AB-2024-MWF-002-2024 AB None None 2024 1 26 \n", + "17 AB-2024-LWF-004-2024 AB None None 2024 1 31 \n", + "18 AB-2024-GWF-003-2024 AB None None 2024 2 23 \n", + "19 AB-2024-GWF-004-2024 AB None None 2024 2 23 \n", + "20 AB-2024-GWF-005-2024 AB None None 2024 2 23 \n", + "21 AB-2024-GWF-006-2024 AB None None 2024 2 23 \n", + "22 AB-2024-SWF-003-2024 AB None None 2024 2 23 \n", + "23 AB-2024-EWF-003-2024 AB None None 2024 2 12 \n", + "24 AB-2024-SWF-002-2024 AB None None 2024 2 22 \n", + "25 AB-2024-SWF-005-2024 AB None None 2024 2 23 \n", + "26 AB-2024-LWF-005-2024 AB None None 2024 2 24 \n", + "27 AB-2024-LWF-006-2024 AB None None 2024 2 26 \n", + "28 AB-2024-EWF-004-2024 AB None None 2024 2 23 \n", + "29 AB-2024-CWF-004-2024 AB None None 2024 2 28 \n", + "30 AB-2024-EWF-005-2024 AB None None 2024 3 3 \n", + "31 AB-2024-SWF-006-2024 AB None None 2024 3 4 \n", + "32 AB-2024-CWF-003-2024 AB None None 2024 2 22 \n", + "33 AB-2024-PWF-003-2024 AB None None 2024 3 5 \n", + "34 AB-2024-PWF-004-2024 AB None None 2024 3 5 \n", + "35 AB-2024-PWF-002-2024 AB None None 2024 2 20 \n", + "36 AB-2024-LWF-007-2024 AB None None 2024 3 8 \n", + "37 AB-2024-SWF-007-2024 AB None None 2024 3 5 \n", + "38 AB-2024-LWF-008-2024 AB None None 2024 3 8 \n", + "39 AB-2024-RWF-002-2024 AB None None 2024 3 11 \n", + "40 AB-2024-HWF-002-2024 AB None None 2024 3 12 \n", + "41 AB-2024-PWF-005-2024 AB None None 2024 3 12 \n", + "42 AB-2024-LWF-009-2024 AB None None 2024 3 13 \n", + "43 AB-2024-PWF-006-2024 AB None None 2024 3 14 \n", + "44 AB-2024-EWF-006-2024 AB None None 2024 3 4 \n", + "45 AB-2024-SWF-009-2024 AB None None 2024 3 17 \n", + "46 AB-2024-GWF-007-2024 AB None None 2024 3 15 \n", + "47 AB-2024-PWF-007-2024 AB None None 2024 3 18 \n", + "48 AB-2024-LWF-013-2024 AB None None 2024 3 19 \n", + "49 AB-2024-SWF-010-2024 AB None None 2024 3 19 \n", + "\n", + " REP_DATE ATTK_DATE OUT_DATE SIZE_HA CAUSE CAUSE2 RESPONSE PRESCRIBED \\\n", + "0 2024-01-02 NaT NaT 0.05 H H None None \n", + "1 2024-01-05 NaT NaT 0.40 H H None None \n", + "2 2024-01-17 NaT NaT 0.01 H H None None \n", + "3 2024-01-09 NaT NaT 0.01 H H None None \n", + "4 2024-01-09 NaT NaT 0.01 H H None None \n", + "5 2024-01-26 NaT NaT 0.67 H H None None \n", + "6 2024-01-30 NaT NaT 5.05 H H None None \n", + "7 2023-01-29 NaT NaT 0.01 U U None None \n", + "8 2024-01-29 NaT NaT 0.01 U U None None \n", + "9 2024-01-15 NaT NaT 0.15 H H None None \n", + "10 2024-01-31 NaT NaT 0.99 H H None None \n", + "11 2024-02-01 NaT NaT 5.60 H H None None \n", + "12 2024-01-08 NaT NaT 0.01 H H None None \n", + "13 2024-02-06 NaT NaT 0.01 H H None None \n", + "14 2024-01-21 NaT NaT 0.10 H H None None \n", + "15 2024-01-30 NaT NaT 0.50 H H None None \n", + "16 2024-01-26 NaT NaT 0.01 H H None None \n", + "17 2024-01-31 NaT NaT 0.02 H H None None \n", + "18 2024-02-23 NaT NaT 72.45 H H None None \n", + "19 2024-02-23 NaT NaT 0.10 H H None None \n", + "20 2024-02-23 NaT NaT 0.01 H H None None \n", + "21 2024-02-23 NaT NaT 0.90 H H None None \n", + "22 2024-02-23 NaT NaT 0.31 H H None None \n", + "23 2024-02-12 NaT NaT 0.01 H H None None \n", + "24 2024-02-22 NaT NaT 0.10 H H None None \n", + "25 2024-02-23 NaT NaT 3.10 H H None None \n", + "26 2024-02-24 NaT NaT 0.01 H H None None \n", + "27 2024-02-26 NaT NaT 0.30 H H None None \n", + "28 2024-02-23 NaT NaT 0.50 H H None None \n", + "29 2024-02-28 NaT NaT 0.01 H H None None \n", + "30 2024-03-03 NaT NaT 0.01 H H None None \n", + "31 2024-03-04 NaT NaT 0.01 H H None None \n", + "32 2024-02-22 NaT NaT 0.10 H H None None \n", + "33 2024-03-05 NaT NaT 0.10 H H None None \n", + "34 2024-03-05 NaT NaT 0.80 H H None None \n", + "35 2024-02-20 NaT NaT 0.04 H H None None \n", + "36 2024-03-08 NaT NaT 0.10 H H None None \n", + "37 2024-03-05 NaT NaT 0.02 H H None None \n", + "38 2024-03-08 NaT NaT 0.01 H H None None \n", + "39 2024-03-11 NaT NaT 0.20 H H None None \n", + "40 2024-03-12 NaT NaT 0.01 H H None None \n", + "41 2024-03-12 NaT NaT 1.31 H H None None \n", + "42 2024-03-13 NaT NaT 0.10 H H None None \n", + "43 2024-03-14 NaT NaT 0.01 H H None None \n", + "44 2024-03-04 NaT NaT 0.01 H H None None \n", + "45 2024-03-17 NaT NaT 0.06 H H None None \n", + "46 2024-03-15 NaT NaT 0.90 H H None None \n", + "47 2024-03-18 NaT NaT 0.20 H H None None \n", + "48 2024-03-19 NaT NaT 0.01 H H None None \n", + "49 2024-03-19 NaT NaT 0.10 H H None None \n", + "\n", + " ACQ_DATE layer omit geometry \n", + "0 2025-04-07 AB_NFDB_2024 None POINT Z (-1345400.786 322485.621 0) \n", + "1 2025-04-07 AB_NFDB_2024 None POINT Z (-1210041.546 1182823.657 0) \n", + "2 2025-04-07 AB_NFDB_2024 None POINT Z (-1194304.684 1023994.495 0) \n", + "3 2025-04-07 AB_NFDB_2024 None POINT Z (-950764.968 883261.867 0) \n", + "4 2025-04-07 AB_NFDB_2024 None POINT Z (-950764.968 883261.867 0) \n", + "5 2025-04-07 AB_NFDB_2024 None POINT Z (-1250605.119 1127058.787 0) \n", + "6 2025-04-07 AB_NFDB_2024 None POINT Z (-1447710.705 715121.493 0) \n", + "7 2025-04-07 AB_NFDB_2024 None POINT Z (-974287.704 983522.99 0) \n", + "8 2025-04-07 AB_NFDB_2024 None POINT Z (-974375.629 983533.158 0) \n", + "9 2025-04-07 AB_NFDB_2024 None POINT Z (-1059792.831 764976.893 0) \n", + "10 2025-04-07 AB_NFDB_2024 None POINT Z (-1371470.078 599531.744 0) \n", + "11 2025-04-07 AB_NFDB_2024 None POINT Z (-1320166.874 850734.753 0) \n", + "12 2025-04-07 AB_NFDB_2024 None POINT Z (-1472349.537 1005693.925 0) \n", + "13 2025-04-07 AB_NFDB_2024 None POINT Z (-1465537.79 745667.573 0) \n", + "14 2025-04-07 AB_NFDB_2024 None POINT Z (-978308.447 1017586.496 0) \n", + "15 2025-04-07 AB_NFDB_2024 None POINT Z (-1352944.19 452606.537 0) \n", + "16 2025-04-07 AB_NFDB_2024 None POINT Z (-977355.502 1017330.27 0) \n", + "17 2025-04-07 AB_NFDB_2024 None POINT Z (-1055717.874 766012.744 0) \n", + "18 2025-04-07 AB_NFDB_2024 None POINT Z (-1419392.874 989377.818 0) \n", + "19 2025-04-07 AB_NFDB_2024 None POINT Z (-1359915.844 937681.2 0) \n", + "20 2025-04-07 AB_NFDB_2024 None POINT Z (-1360051.378 937310.804 0) \n", + "21 2025-04-07 AB_NFDB_2024 None POINT Z (-1444320.741 1044537.904 0) \n", + "22 2025-04-07 AB_NFDB_2024 None POINT Z (-1266330.556 843866.256 0) \n", + "23 2025-04-07 AB_NFDB_2024 None POINT Z (-1360172.099 754180.241 0) \n", + "24 2025-04-07 AB_NFDB_2024 None POINT Z (-1131841.066 932218.414 0) \n", + "25 2025-04-07 AB_NFDB_2024 None POINT Z (-1245469.982 886731.678 0) \n", + "26 2025-04-07 AB_NFDB_2024 None POINT Z (-1153484.509 854359.055 0) \n", + "27 2025-04-07 AB_NFDB_2024 None POINT Z (-1059544.113 752819.06 0) \n", + "28 2025-04-07 AB_NFDB_2024 None POINT Z (-1484950.357 841396.879 0) \n", + "29 2025-04-07 AB_NFDB_2024 None POINT Z (-1349725.487 454349.403 0) \n", + "30 2025-04-07 AB_NFDB_2024 None POINT Z (-1456865.625 739522.295 0) \n", + "31 2025-04-07 AB_NFDB_2024 None POINT Z (-1187243.213 1028659.049 0) \n", + "32 2025-04-07 AB_NFDB_2024 None POINT Z (-1378893.055 448845.726 0) \n", + "33 2025-04-07 AB_NFDB_2024 None POINT Z (-1302860.745 1011527.785 0) \n", + "34 2025-04-07 AB_NFDB_2024 None POINT Z (-1305953.361 1009063.084 0) \n", + "35 2025-04-07 AB_NFDB_2024 None POINT Z (-1316353.752 1014522.535 0) \n", + "36 2025-04-07 AB_NFDB_2024 None POINT Z (-1088892.243 804111.541 0) \n", + "37 2025-04-07 AB_NFDB_2024 None POINT Z (-1221168.565 888872.073 0) \n", + "38 2025-04-07 AB_NFDB_2024 None POINT Z (-965480.692 725071.516 0) \n", + "39 2025-04-07 AB_NFDB_2024 None POINT Z (-1352491.23 606371.113 0) \n", + "40 2025-04-07 AB_NFDB_2024 None POINT Z (-1262695.951 1277707.595 0) \n", + "41 2025-04-07 AB_NFDB_2024 None POINT Z (-1406771.122 1089375.802 0) \n", + "42 2025-04-07 AB_NFDB_2024 None POINT Z (-951370.69 883143.638 0) \n", + "43 2025-04-07 AB_NFDB_2024 None POINT Z (-1322677.547 1101879.136 0) \n", + "44 2025-04-07 AB_NFDB_2024 None POINT Z (-1368206.328 743441.56 0) \n", + "45 2025-04-07 AB_NFDB_2024 None POINT Z (-1246445.666 889134.341 0) \n", + "46 2025-04-07 AB_NFDB_2024 None POINT Z (-1358677.001 892209.033 0) \n", + "47 2025-04-07 AB_NFDB_2024 None POINT Z (-1379949.504 1055572.462 0) \n", + "48 2025-04-07 AB_NFDB_2024 None POINT Z (-1011996.534 745868.235 0) \n", + "49 2025-04-07 AB_NFDB_2024 None POINT Z (-1133745.417 933310.31 0) " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Load the shapefile\n", + "gdf = gpd.read_file(shapefile)\n", + "\n", + "# Display selected columns for first 50 records\n", + "selected_columns = [\n", + " \"NFDBFIREID\",\n", + " \"SRC_AGENCY\",\n", + " \"NAT_PARK\",\n", + " \"FIRENAME\",\n", + " \"YEAR\",\n", + " \"MONTH\",\n", + " \"DAY\",\n", + " \"REP_DATE\",\n", + " \"ATTK_DATE\",\n", + " \"OUT_DATE\",\n", + " \"SIZE_HA\",\n", + " \"CAUSE\",\n", + " \"CAUSE2\",\n", + " \"RESPONSE\",\n", + " \"PRESCRIBED\",\n", + " \"ACQ_DATE\",\n", + " \"layer\",\n", + " \"omit\",\n", + " \"geometry\",\n", + "]\n", + "\n", + "gdf[selected_columns].head(50)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a65de9e3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total prescribed burns (CAUSE == 'H-PB'): 353\n" + ] + } + ], + "source": [ + "# Count how many rows have CAUSE == 'H-PB'\n", + "prescribed_burns = gdf[gdf[\"CAUSE\"] == \"H-PB\"]\n", + "print(\"Total prescribed burns (CAUSE == 'H-PB'):\", len(prescribed_burns))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3aa35f79-98f3-4800-9fec-ed8c0ed47443", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/2_data_preparation/README.md b/2_data_preparation/README.md index 58add43a2..650daf953 100644 --- a/2_data_preparation/README.md +++ b/2_data_preparation/README.md @@ -1 +1,87 @@ -# Data Preparation + +# Prescribed Burns and Wildfire Risk Mitigation in Canada + +## Project Overview + +Wildfires are becoming more frequent and severe in Canada due to climate change. +One method used to reduce risk is prescribed burning: controlled fires that +reduce fuel loads in forests. Our project explores whether satellite imagery +and open data can help identify areas suitable for future prescribed burns, + using historical fire patterns and environmental features. + +## Research Question + +**How does the integration of satellite imagery improve the outcomes of +prescribed burning programs in mitigating wildfire risk in Canada?** + +## Problem Modeling Approach + +We are modeling our problem by combining multiple datasets to identify patterns +in areas treated with prescribed burns and those impacted by wildfires. +Since precise data on prescribed burn locations is limited, + we are constructing a proxy dataset using: + +- Parks Canada records for annual prescribed burn area +- ONFIRE dataset to estimate approximate locations and timeframes of prescribed burns +- Satellite imagery before and after the estimated burn period to extract +- environmental and visual features (e.g., vegetation density, moisture, fire scars) + +By comparing features from these regions with those from areas affected by large +wildfires, we aim to train a model that can recommend suitable regions for +future prescribed burns. + +## Data Sources Used + +We are leveraging the following publicly available datasets: + +- Canadian National Fire Database (CNFDB) for historical wildfire locations and sizes +- Parks Canada prescribed burn records for yearly treatment area information +- ONFIRE gridded dataset, which includes coarse-resolution prescribed burn indicators +- Satellite imagery (e.g., Sentinel-2, Landsat) to analyze pre- and post-burn conditions + +## Modeling Strategy + +Our strategy includes the following steps: + +1. Identify likely prescribed burn locations using ONFIRE gridded fire records + marked as prescribed burns (H-PB). +2. Cross-reference with Parks Canada reported burn areas to refine potential + prescribed sites. +3. Download satellite images for estimated burn areas, both before and after + the burn date. +4. Extract features such as vegetation indices (NDVI), land cover types, + and burn severity indicators. +5. Build a machine learning model that compares these areas to known wildfire + zones without prescribed burns. +6. Use the model to highlight areas where prescribed burning could reduce the + risk of future uncontrolled wildfires. + +## Assumptions and Limitations + +In this project, we made several assumptions: + +- ONFIRE grid cells marked as prescribed burns are reasonably accurate + representations of actual burn areas. +- Parks Canada data provides a valid proxy for regional prescribed burn + activity, even though it lacks spatial granularity. +- Satellite imagery reflects observable changes due to prescribed burning, + and these changes are detectable using available features. +- Our analysis may not capture smaller or undocumented burns and excludes local + management or socio-political constraints. + +We acknowledge that data on prescribed burn locations is not always detailed or + complete. This presents limitations in spatial precision and may affect model + accuracy. We will document and evaluate these limitations as part of our + project outcomes. + +## Future Work + +In future stages of the project, we aim to: + +- Improve identification of prescribed burn areas through spatial analysis and + enhanced remote sensing techniques +- Test our model on selected high-risk regions to evaluate predictive performance +- Engage with fire management experts or agencies to validate assumptions and + potentially acquire more granular data +- Expand the model to incorporate additional environmental variables, + including weather and topography diff --git a/Exploring_Kittens.png b/Exploring_Kittens.png new file mode 100644 index 000000000..e63451a9e Binary files /dev/null and b/Exploring_Kittens.png differ diff --git a/LICENSE b/LICENSE index 6e628e40e..d04b03511 100644 --- a/LICENSE +++ b/LICENSE @@ -1,4 +1,4 @@ -MIT License +# MIT License Copyright (c) 2024 MIT Emerging Talent diff --git a/README.md b/README.md index e69de29bb..cc4ff56db 100644 --- a/README.md +++ b/README.md @@ -0,0 +1,79 @@ +# Collaboration + +## Group Norms Summary + +Just like the game it is based on (Exploding Kittens), Exploring Kittens +is a fun-loving group of researchers who want to explore the world. +Our goal is to help each other, learn from one another, and grow together +as we explore the world of Computer and Data science. + +## Deforestation Analysis in Malaysia + +Nowadays, deforestation in Malaysia has reached an unprecedented level. +Every day and every year, several more percent of the country's +area is deforested, affecting millions of people in rural areas. + +With our new advances in image analysis, we aim for detailed quantification and +localization of the deforestation process. We also intend to study +its correlation with parameters of citizen well-being. + +Our group decided to focus on this research domain due to extensive experience. +In particular, Alona is a life sciences major with several courses in ecology, biology, +and data processing. Zaid has successfully completed data analysis projects and +possesses extensive knowledge of deforestation effects on rural communities in Malaysia. + +Which particular correlation exists between rural households' +well-being and the current deforestation status of their +area (e.g., has it been deforested long ago, recently, or not at all)? + +The analysis project should take several weeks. Processing will be executed on personal +computers or cloud services. Data will be limited to information +openly available at: + +- [Global Forest Watch](https://www.globalforestwatch.org/) +- [Google Earth Engine](https://earthengine.google.com/) + +See more details here: +[Project Guide]( +/ET6-CDSP-group-27-repo-Exploring_Kittens/ +blob/main/0_domain_study/guide.md) + +## Group Agreements (Intention-Based) + +- Open and respectful communication between members. Voices are not equally +loud but they are equally important. +- Consistent collaboration. We expect members to regularly participate and +contribute to the group. +We will however also be understanding if a member +needs some time off due to personal or professional commitments. +- Punctuality. We should expect to wait no more than 5 minutes for meetings +to start and people to be present. +- Curiosity. We all come from different backgrounds and places, +the only bad questions we can ask are questions that have been answered. +- Togetherness. Our group members are supportive of one another's needs, feelings +or circumstances. No one in the group is alone. +- Adaptibility. We are more focused on identifying solutions rather than +complaining about the problems or pointing fingers. We will be quick to change +our approach or methodology if need be. +- Respect. We are all human, we are all equal. We intend to value everyone's +time, commitments, and resources just like we value our own. +- Humor. Jokes are encouraged, we will strive to keep the atmosphere light +and refreshing so that meetings don't feel like a drag. +- Communication. We don't expect members to reply in real time, but +a response to messages or questions should have a reply in a day, +no more than 2 if the member is busy. +- Exploding Kittens. We will one day all play a game of Exploding Kittens +together. + +## Research Question + +### How effective is Satellite Image Analysis at Predicting Deforestation in Malaysia? + +- Research has real world implications for conservation +efforts not just in Malaysia but globally. +- Satellite image analysis is closely tied to the field of +data science and programming. +- Prediction of deforestation allows for proactive measures +for conservation rather than reactive measures. + +![Alt text](Exploring_Kittens.png) diff --git a/collaboration/README.md b/collaboration/README.md deleted file mode 100644 index 20889b951..000000000 --- a/collaboration/README.md +++ /dev/null @@ -1,5 +0,0 @@ -# Collaboration - - - - diff --git a/collaboration/communication.md b/collaboration/communication.md index f9e2d0181..79d8bdaad 100644 --- a/collaboration/communication.md +++ b/collaboration/communication.md @@ -15,32 +15,39 @@ | Day | How | The topic of discussion | | :----: | :-: | ----------------------: | -| | | | +| June 2nd | Google Meet | Respecting deadlines, collaboration | ## Communication Channels How often we will get in touch on each channel, and what we will discuss there: -- **Issues**: -- **Pull Requests**: -- **Slack/Discord**: -- **Video Calls**: +- **Issues**: To be discussed +- **Pull Requests**: Every day +- **Slack/Discord**: Every day +- **Video Calls**: Every 3 days ## Availability ### Availability for calling/messaging -| Day | Mon | Tue | Wed | Thu | Fri | Sat | Sun | -|--------|:---:|:---:|:---:|:---:|:---:|:---:|:---:| -| _name_ | | | | | | | | +| Day | Mon | Tue | Wed | Thu | Fri | Sat | Sun| +|-------|:-----:|:------:|:------:|:------:|:-----:|:---:|:----:| +| Alona |5–8 PM | 5–8 PM | 3–8 PM | 5–8 PM | 5–8 PM| No |9–8 PM EST| +| Asia |5–10 PM| 5–10 PM| 5–10 PM| 5–10 PM| No | 5–10 PM| 5–10 PM | +| Vahab |10–14 *| 10–14 *| 10–14 *| 10–14 *| 10–14 *| Can't plan in advanced|| +| Zaid| 7 PM-11 AM EST|7 PM-10 AM EST|7 PM-8 AM EST|7 PM-8 AM EST|No|No|No| +|Jeffery | 2-6 PM | 10-6 PM | 2-6 PM| 2-6 PM | No | 10-4 PM| 2- 6 PM GMT| + +\* Subject to change depending on other commitments. +Currently based in **Canada (Edmonton Time Zone - MST/MDT)**. +In **June**, located in **Central European Time Zone (CET/CEST)**. ### How many hours everyone has per day -- name: _5h_ -- name: _6h_ -- name: _5h_ -- name: _4h_ -- name: _3h_ +- Alona: _3h_ +- Vahab: _4h_ weekdays. +- Zaid: _3h_ +- Jeffery: _3h_ ## Asking for Help diff --git a/collaboration/constraints.md b/collaboration/constraints.md index 24079505c..905fc0724 100644 --- a/collaboration/constraints.md +++ b/collaboration/constraints.md @@ -15,6 +15,14 @@ Some boundaries around our project. - ... --> +- *Deadlines Set by MIT-ET* + The schedule and priorities of the project are largely influenced by + deadlines established by MIT-ET. + +- *Organizational Requirements* + MIT-ET enforces specific tools, workflows, and approval processes that + the team must adhere to. + ## Internal: Involuntary +- *Differences in Skill Levels* + Team members have varying levels of experience in Python, programming, and + collaboration tools, requiring additional time for knowledge sharing and + onboarding. + +- *Limited Availability* + Some members manage full-time jobs or family responsibilities, + reducing their availability for meetings, reviews, or coding sessions. + +- *Unexpected Disruptions* + Personal issues or emergencies may occasionally hinder + participation or delay deliverables. + +- *Workload Imbalance* + Uneven contribution may occur, with some members needing to take on + extra tasks due to others' limited availability. + ## Internal: Voluntary + +- *Agreed-Upon Coding Standards* + The team has chosen to follow consistent coding conventions + to improve readability and maintainability. + +- *Standardized Git Workflow* + A version control strategy recommended by MIT-ET has been + adopted to ensure consistency and traceability. + +- *Task Prioritization Approach* + The group aligns on priorities, sets milestones, and commits + to internal deadlines. + +- *Commit Message Format* + Members use a unified format for commit messages + to maintain clarity and track changes effectively. + +- *Mandatory Peer Code Reviews* + All pull requests must be reviewed and approved by at least + one or two members before merging into the main branch. diff --git a/collaboration/learning_goals.md b/collaboration/learning_goals.md index 11c583d2b..29d69e356 100644 --- a/collaboration/learning_goals.md +++ b/collaboration/learning_goals.md @@ -2,4 +2,51 @@ ## Collective +- Learn how to find, analyze, and critically assess academic +research and other credible sources. +- Use previously acquired statistical knowledge to + analyze data and build real models. +- Learn to accurately define research problems and +design appropriate methodologies to address them. + ## Individual + +### Alona + +- Understand and learn the collaboration work process while + working on the group project in GitHub +- Gain experience in reviewing others' work and + contributing to open-source projects confidently. +- Improve collaboration skills by participating in group + projects, sharing ideas clearly, and communicating with the team. + +### Asia + +- I can improve my GitHub skills. +- Managing my time to meet deadlines. +- Gaining more knowledge and confidence dealing with different people. + +### Vahab + +- Understand how to use real-world data to define problems and uncover insights. +- Practice building models that help explain or solve real-world issues. +- Learn to use Jupiter Notebooks effectively for data exploration and modeling. +- Gain confidence in documenting, sharing, and communicating data science work clearly. + +### Zaid + +- Refresh my GitHub and Python skills. +- Learn something new. +- Improve my teamwork abilities. +- Gain experience working with vastly different time zones. + +### Jeffery + +- Strengthen my ability to translate complex problems +into actionable data science tasks. + +- Improve my skills in managing and coordinating collaborative coding projects +on GitHub. + +- Deepen my understanding of asynchronous programming and +how to apply it effectively in group collaborative projects. diff --git a/collaboration/meeting_agenda.md b/collaboration/meeting_agenda.md new file mode 100644 index 000000000..f1776dde7 --- /dev/null +++ b/collaboration/meeting_agenda.md @@ -0,0 +1,193 @@ + +# Meetings agenda + +--- + +## Communication Schedule + +| Day | How | The topic of discussion | +| :----: | :-: | ----------------------: | +| June 2nd | Google Meet | Respecting deadlines, collaboration | +| June 6th | Google Meet | Brainstorming questions | +| June 11th | Google Meet | Presenting questions and choosing one | +| June 15th| Google Meet | Finalising group research topic | +| June 20th| Google Meet | Planning milestone 2 | + +## Content of each meeting + +--- + +### June 6th, 2 PM + +- How to define a question + - Be very specific + - Expect your question to change while doing more research +- Domain of interest of group members +- Choosing the right research question + - Keep availability of data in mind +- Ideas to use image analysis + - Explored applying image analysis in research domains like: + - Deforestation + - Biology + - Healthcare +- Consider difficulty of research question when proposing + - Too easy > Too difficult +- Elaborate on image analysis + +**_What to prepare for the next meeting?_** + +- On Wednesday, come to the meeting with one or more research questions +- Investigate whether image analysis is feasible or too difficult + +--- + +### June 11th, 5PM EST + +#### Key Discussion Points + +##### Proposed Research Questions + +1. How can online access to education support learning continuity during +pandemics and humanitarian crises such as refugee displacement? +2. What is the impact of wildfire exposure on respiratory health in Canada, + and how can it be quantified? +3. To what extent can the use of antidepressants and economic indicators in +small economies reflect the overall happiness and mental well-being of a population? +4. Can natural language processing (NLP) techniques be used to classify judicial +decisions as punitive or restorative based on the language in court judgments? +5. How effective is image analysis in detecting early signs of deforestation as +an indicator of climate change? + - Use vegetation index to train model. + - Many free images over several years are available online (1984–today). + - Recommended dataset: Global Forest Watch (2000–present). + - Consider region-bound analysis. + - Optionally incorporate air quality data from WorldAQ (e.g., CO₂ spikes as indicators). + +##### Platform Migration + +It was agreed that all ongoing chats and discussions will move to _Slack_ to +ensure better tracking and visibility for the MIT team. + +##### Next Steps + +- A follow-up meeting is scheduled for tomorrow to finalize the research topic. +- _Asia_ suggested that each member brings at least one research topic idea +to the next meeting. +- The group will then brainstorm collectively to narrow the suggestions down to +a concise, group-approved research focus. + +--- + +### June 15th, 5PM EST + +#### Review of Identified Group Research Topic + +- Final confirmation of the selected research topic; "How effective is Satellite +Image Analysis at Predicting Deforestation in Malaysia?" +- Clarification of objectives and scope + +#### Distributed Group Work + +- Task allocation and responsibilities +- Timeline and milestones leading up to **June 16** deadline + +#### Planning for the Next Meeting + +- Agreed on next meeting date, June 16th, 2025. + +#### Collaboration Folder Setup + +- All members are encouraged to complete their tasks in the collaborations +folder as soon as possible. + +--- + +### June 20th, 2025 + +#### Meeting Summary + +**Context:** This meeting took place shortly after the start of Milestone 2 data + collection on June 17th. +**Participants:** Asia, Zaid, Vahab. A recording has been shared with the rest of + the team. + +#### Agenda + +- Planning the milestone and going over key deliverables. + +#### Discussion Highlights + +- We went through the list of deliverables for this milestone. +- As a group, we agreed to focus on what’s the most important and possibly most + challenging deliverable: + _“A non-technical explanation of how you chose to model your domain, and + possible flaws in this approach, in your README (visuals can be very helpful!).”_ +- Evan asked for a bit more clarity around our research question—specifically, + which satellite we're focusing on and what kind of deforestation we plan to study. +- We talked about the need for improving our understanding of our research + domain and creating a plan to model our data. +- To do that, we’ll need to build a better understanding of the domain. + Some key questions to start with: + - What is the definition of deforestation? + - What are the different causes of deforestation? + - What kinds of data or indicators do we need to track it? + - _[Feel free to add any other helpful questions that can help with domain modeling.]_ + +#### Steps to take + +- Aim to finish this part of the deliverable by **Monday, June 23rd**, to allow + time for an expert session with ET if needed. +- The team would appreciate short daily check-ins to help stay on track and + avoid a last-minute rush. + +--- + +### Meeting Agenda + +#### 1. Topic Change Discussion + +The group agreed to adopt a new research topic proposed by Vahab: +**"Prescribed Fire Planning to Prevent Wildfires in Canada using Satellite +Images."** _(Thunderstorms are the biggest reason for wildfires in North America.)_ + +#### 2. Key Concerns and Considerations + +- The group acknowledged the importance of clearly defining the scope +and ensuring the topic has real-world relevance. +- Alona pointed out that the new topic lacks a strong **social impact** +compared to those discussed in lecture slides. +- She also noted the absence of an “**x maps to y**” correlation present in +previous topics. +- The group emphasized the need for **concise data collection**. +- There was consensus to **limit the geographical scope to Canada** (for now) +to keep the project focused and manageable. + +#### 3. Refining the Research Question + +Proposed refined versions of the research question: + +- _How does the integration of satellite imagery improve the outcomes of +prescribed burning programs in mitigating wildfire risk in Canada?_ +- _How effective are prescribed forest fires by satellite images in reducing +the risk of out-of-control wildfires in Canada?_ + +#### 4. Immediate Action Items + +- The new topic will be discussed with **Evan on Slack** to confirm +its acceptability. +- **Asia** identified similar research projects and GitHub repositories for +insight and inspiration. +- Ongoing discussion around the **specific data types** needed for the project. + +#### 5. Task Assignments + +- **Vahab** will refine the group README and submit a pull +request with the updated content. +- **Alona** will create a format for group member retrospectives +and begin coordinating task assignments for upcoming deadlines. + +## 6. Next Meeting + +- **Date:** June 29, 2025 +- **Time:** 1:00 PM EST +- **Agenda:** Team members will report on progress and discuss feedback from Evan. diff --git a/collaboration/retrospective.md b/collaboration/retrospective.md deleted file mode 100644 index c24b796a7..000000000 --- a/collaboration/retrospective.md +++ /dev/null @@ -1,31 +0,0 @@ - - -# Retrospective - -## Stop Doing - -## Continue Doing - -## Start Doing - -## Lessons Learned - ---- - -## Strategy vs. Board - -### What parts of your plan went as expected? - -### What parts of your plan did not work out? - -### Did you need to add things that weren't in your strategy? - -### Or remove extra steps? - ---- - -## Individual Rerospectives - -### Name - - diff --git a/collaboration/retrospective_milestone1.md b/collaboration/retrospective_milestone1.md new file mode 100644 index 000000000..4a8e81c9a --- /dev/null +++ b/collaboration/retrospective_milestone1.md @@ -0,0 +1,73 @@ +# Retrospective Milestone 1 + +## Stop Doing + +- Not consistently documenting tasks and discussions on the project board. +- Joining meetings without sufficient preparation. +- Strictly enforcing the 80-character line limit in CI checks + +## Continue Doing + +- Doing an excellent job brainstorming ideas and questions, supporting +each other and actively discussing one another’s topics, helping +verify research novelty and suggesting additional ideas. +- Holding meetings regularly despite significant time zone +differences. +- Helping each other with GitHub setup and efficiently distributed tasks +among the active team members. + +## Start Doing + +- Using the group project board. +- Start organizing the workflow from the very beginning of the project. +- Better configure pull request policy + +## Lessons Learned + +- Sharing useful resources, including free datasets, among team members. +- Discussing topics like image analysis and antibiotics misuse to explore +different domains. +- Taking into account the different time zones of each team member is +important when planning meetings and deadlines. + +--- + +## Strategy vs. Board + +### What parts of your plan went as expected? + +- Excellent team work of active participants as well as excellent asynchronous work + +### What parts of your plan did not work out? + +- While generating many interesting research questions across domains, we +experienced delays in choosing a focus area — next time, we’ll aim for a +more time-efficient and organized selection process. + +### Did you need to add things that weren't in your strategy? + +- There are varying levels of engagement, with some members missing live +meetings and recordings + +--- + +## Individual Retrospectives + +### Alona + +- Did a great job with divergent thinking and came up with several + original research questions. +- Actively participated in organizing the team’s work and discussing + other group members’ questions. +- Made progress in convergent thinking. +- Still needs to improve the skill of conducting preliminary +research before formulating a question. +- Returned Bernard the cat to its owners + +### Zaid + +- Was able to contribute an interesting research question and participated +in productive discussion. +- Found lots of good data. +- Didn't do much divergent thinking as I was too intrigued by one question. +- Need to improve my GitHub skills and learn how to use the project board properly. diff --git a/collaboration/retrospective_milestone2.md b/collaboration/retrospective_milestone2.md new file mode 100644 index 000000000..a25dd3778 --- /dev/null +++ b/collaboration/retrospective_milestone2.md @@ -0,0 +1,58 @@ +# Retrospective Milestone 2 + +## Stop Doing + +- Discussing important topics in WhatsApp instead of using structured + platforms. +- Starting a milestone without a clear and detailed work plan. + +## Continue Doing + +- Actively collaborating within the team. +- Staying open to new ideas and discussing them collectively. +- Distributing tasks fairly and completing them on time. + +## Start Doing + +- Making better use of the GitHub project board for tracking progress + and responsibilities. +- Documenting key decisions and discussions in issues or the project wiki. + +## Lessons Learned + +- Early brainstorming sessions helped us identify knowledge gaps and + adjust our research focus in time. +- Clear task ownership reduces confusion and prevents duplication of work. +- Regular check-ins, even short ones, help maintain momentum and keep + everyone aligned. +- Writing things down — such as decisions, questions, and progress updates — + improves accountability and makes it easier to onboard less active members. +- Too much flexibility in the beginning leads to delays; it’s better to + define roles and timelines early on. + +## Strategy vs. Board + +### What parts of your plan went as expected? + +- *(To be completed)* + +### What parts of your plan did not work out? + +- We identified a strong research question supported by a rich dataset, + but decided to change it at the last minute. + +### Did you need to add things that weren't in your strategy? + +- Team engagement levels varied. Some members missed live meetings and + didn’t catch up by watching the recordings, which slowed down overall + progress. + +## Individual Retrospectives + +### Alona + +- Analyzed sample research questions and actively contributed to + discussions around teammates' ideas. +- Helped improve and refine the work of other team members. +- Next time, will focus more on the project during critical periods and + stay more mindful of deadlines. diff --git a/collaboration/retrospective_milestone_0.md b/collaboration/retrospective_milestone_0.md new file mode 100644 index 000000000..6f8599552 --- /dev/null +++ b/collaboration/retrospective_milestone_0.md @@ -0,0 +1,88 @@ +# Retrospective milestone 0 + +## Stop Doing + +- Letting tasks and discussions remain informal without proper + documentation on the project board. +- Wasting time revisiting issues that could have been + prevented through more structured workflows. +- Not planning the milestone steps in detail at the beginning, + which leads to confusion mid-way. +- Staying silent about availability or progress on assigned tasks, + which creates uncertainty for the rest of the team. + +## Continue Doing + +- Maintaining clear and effective communication via the WhatsApp group. +- Holding productive group and one-on-one meetings through Google Meet. +- Actively sharing knowledge and resources to minimize + information gaps within the team. + +## Start Doing + +- Encouraging full participation from all members in both + discussions and task execution. +- Scheduling regular review sessions to stay aligned with project goals. +- Planning milestones and necessary steps earlier, to avoid rushed. +- Having short daily check-ins (written, not meetings) to update each other + on progress and blockers. + +## Lessons Learned + +- Strong and consistent group communication is crucial to project success. +- Clearly defined roles and responsibilities lead to better accountability. +- Completing tasks ahead of deadlines allows time for reviews, + feedback, and revisions. +- Retrospectives can be used to break down complex challenges, +giving everyone the opportunity to contribute, learn, +and gain confidence in solving similar problems in the future. +- Time zone differences are challenging, but with patience and structure, + they can be managed effectively. + +--- + +## Strategy vs. Board + +### What parts of your plan went as expected? + +- Clear communication channels, such as WhatsApp and Google + Meetings, worked well for collaboration. + +### What parts of your plan did not work out? + +- Group meetings were not reflected on the project board. + +### Did you need to add things that weren't in your strategy? + +- Some group members did not respond, which caused delays + and negatively affected collaboration. + +--- + +## Individual Retrospectives + +### Alona + +- Good organizational work was done. +- Collaborated willingly with other members. +- There are opportunities for growth in time management. + +### Asia + +- I can improve my GitHub skills. +- Collaboration on tasks saved us a lot of time + +### Zaid + +- Definitely needed the GitHub refresher. +- Timezones are a challenge, but if everyone is willing to compromise, +it can be overcome. + +### Vahab + +- Time differences are challenging, but we’re figuring out ways to adapt, + We can do better. +- I see the need to plan better at the beginning of each milestone. +- The team is very supportive and flexible, which really helps when + things get off track. + \ No newline at end of file