SDG Mapping Prototype_Administative

Outreachy_Nwajiunor_2023/Task 2/Nwajiunor_Task 2_SDG_Mapping_Prototype_Documentation.md

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+## SDG Mapping Prototype
+
+This document presents prototypes for mapping Sustainable Development Goals (SDGs) within the administrative land sector dataset. Each section provides information about the dataset under consideration, the attribute considered, the idea for mapping, and the resulting outcomes.
+
+The two SDGs chosen in relevance to the administrative land sector dataset category are Goal 11 and Goal 15.
+
+Goal 11: Sustainable Cities and Communities. It is about making cities and human settlements inclusive, safe, resilient and sustainable. While Goal 15: Life on Land. It is about conserving life on land. It is to protect and restore terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and stop biodiversity loss.
+
+## Administrative Land Sector Dataset
+
+### World Soil Boundary
+
+#### SDG 15: Life on Land
+
+#### Dataset Attribute:
+
+- `IPCC`: IPCC stands for Intergovernmental Panel on Climate Change. The soil names are classified based on the IPCC classification.
+
+#### Mapping Explanation:
+
+- `Mapped_SDGs`: This column results from mapping and associates each soil resource (type) with its relevant SDG. In other words, it helps identify which specific SDG(s) are relevant to different soil types, with all 33 soil resources (types) being mapped to SDG 15: Life on Land due to their alignment with this goal's targets.
+
+SDG 15: Life on Land: This SDG is associated with various soil types listed in the world soil resources dataset. It suggests that these soil types are directly related to SDG 15, which focuses on protecting, restoring, and promoting the sustainable use of terrestrial ecosystems found on the earth's surface.
+
+### World Protected Areas
+
+#### SDG 11: Sustainable Cities and Communities & SDG 15: Life on Land
+
+#### Dataset Attribute
+- `OWN_TYPE`: This column refers to the ownership type or category for the world protected areas. 
+
+#### Mapping Explanation:
+
+- `Mapped_SDGs`: This column associates each ownership type with its relevant SDG. This mapping helps in identifying which SDGs are being addressed by various protected areas, providing insights into the contributions of these areas to global sustainability goals.  Some entries (ownership type) are not mapped to any SDG, indicating that they might not have a direct link with the two relevant SDGs identified for this task, some others were mapped to SDG 11: Sustainable Cities and Communities and the rest were mapped to SDG 15: Life on Land. The number of enteries that were not mapped were 188415 and those that were mapped to SDG 15 were 51686. Only 64 were mapped to SDG 11.
+
+SDG 11: Sustainable Cities and Communities: This SDG is associated with the "for-profit organisations" ownership type as their involvement could influence urban development in cities and communities. 
+
+SDG 15: Life on Land: This SDG is associated with the "Non-profit organisations", "Individual landowners", "Multiple ownership", "Communal", and "Joint ownership" categories. These ownnership types have impact on the protect areas for biodiversity conservation, land protection and management of natural areas.
+
+Not Mapped: This indicates that these protected areas did not fit the criteria for direct mapping to either of the relevant SDG for this task. Ownership types that fall under this is the "Not Reported" and "Contested" categories. It is challenging to link the "Not Reported" category to the relevant SDG without more information, as well as the "Contested" category because nature of the disputes and their implications for land conservation cannot be ascertained.
+
+### Roads
+
+#### SDG 11: Sustainable Cities and Communities
+
+#### Dataset Attribute
+- `FCLASS`: This column refers to the column, which represents functional road types. They are represented with integers from 0 - 6. The different road types represented with integers are defined as follows; 1=Highway, 2=Primary, 3=Secondary, 4=Tertiary, 5=Local/Urban, 6=Trail, 0=unspecified.
+
+#### Mapping Explanation:
+
+- `Mapped_SDGs`: This column associates each functional road type with its relevant SDG. This mapping helps in identifying which SDGs are being addressed by various protected areas, providing insights into the contributions of these areas to global sustainability goals. All enteries (functional classes) were mapped to SDG 11 which equated to a total of 1101300. 
+
+SDG 11: Sustainable Cities and Communities: The functional road types are all related to urban and rural infrastructure, transportation, and accessibility within cities and communities. Therefore,they can map be mapped to SDG 11, as it addresses the goal of making cities and human settlements inclusive, safe, resilient, and sustainable. The different road types are essential components of urban and rural infrastructure, and their quality and accessibility are important factors in achieving this sustainability goal.
+
+[To access the saved mapped datasets for each section of the administrative land sector category, click on this link.](https://drive.google.com/drive/folders/1ZGqZaco55mJDn8uVXH6Y6l3DcVe-Gu6m?usp=share_link)
+
+#### References
+
+These references aided the research process for this task. 
+
+[SDGs Definition by UNDP](https://www.undp.org/sustainable-development-goals#:~:text=What%20are%20the%20Sustainable%20Development,people%20enjoy%20peace%20and%20prosperity)
+
+[SDG 11](https://www.un.org/sustainabledevelopment/cities/#:~:text=Goal%2011%3A%20Make%20cities%20inclusive%2C%20safe%2C%20resilient%20and%20sustainable&text=Goal%2011%20is%20about%20making,half%20living%20in%20urban%20areas)
+
+[SDG 15](http://wdpa.s3.amazonaws.com/WDPA_Manual/English/WDPA_Manual_1_4_EN_FINAL.pdf)
+
+[Unprecedented Rates of Mountain Glacier Melting](https://www.genevaenvironmentnetwork.org/resources/updates/unprecedented-rates-of-mountain-glacier-melting/)
+
+[World Database of Protected Areas](http://wdpa.s3.amazonaws.com/WDPA_Manual/English/WDPA_Manual_1_4_EN_FINAL.pdf)
+
+[Global Roads Open Access Dataset Documentation](https://sedac.ciesin.columbia.edu/downloads/docs/groads/groads-v1-documentation.pdf)
+

Outreachy_Nwajiunor_2023/Task 3/Nwajiunor_Task 3_Brief Report_Geospatial Analysis.md

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+## Report on Geospatial Analysis of Administrative Land Sector Data
+
+### Introduction
+
+The following report provides a comprehensive overview of the spatial analysis conducted on the administrative land sector dataset. This dataset encompasses diverse subcategories, including information regarding the world's soil boundaries, global protected areas, and the extensive global road network. The analysis aims to identify spatial patterns, correlations, and critical insights within these datasets.
+
+### Protected Areas Mapping Issue
+
+One of the key components of the analysis focused on mapping protected areas around the world. However, during the process, a critical issue arose, primarily related to the geometry of the dataset. This geometry issue was primarily due to problems with the spatial components that define the shape and location of each protected area, known as geometries. The `geometry` column included a large number of invalid geometries. This prevented the successful creation of a map for the protected areas dataset. Such issues can arise due to data entry errors, inconsistencies in spatial representations, or other data quality problems.
+
+### Key Findings and Insights
+
+Despite this challenge, the analysis provided several noteworthy findings and insights. High Activity Clay Soils (HAC) emerged as prominent soil resources, with distinctive relevance. These soils, characterized by their 2:1 silicate clay mineral dominance, were uniquely mapped as a "combination" under both the `ecosystem_type` and `major_ecosystem_service` columns due to their diverse soil resource composition.
+
+A comprehensive overview of protected areas indicated that the dataset comprises 188,413 globally recognized designations. Interestingly, a substantial proportion of these areas lack reported ownership structures, while two contested protected areas are identified. These discoveries underline the need for comprehensive reporting and improved management of protected areas.
+
+The global road network analysis revealed significant regional variations in road types. The functional class "unspecified" featured prominently, indicating the importance of enhanced classification and data reporting. Notably, North America exhibited a high prevalence of paved road types, while East Africa demonstrated a diverse range of road surfaces, including dirt/sand roads, paved roads, gravel roads, and unspecified roads.
+
+The relationship between soil types and major ecosystem services was explored, unveiling insights into the ecological roles of various soil varieties. Tropical forest ecosystems dominated in regions like Africa and South America, with "Anthrosol" standing out for its human-influenced ecosystem type.
+Additionally, the boundaries within the world soil resources dataset highlighted the intersections of different ecosystem types and services, emphasizing their significance for ecological interactions and protected area management.
+
+### Conclusion and Actionable Key Points
+
+In conclusion, despite the challenges encountered, the spatial analysis of administrative land sector data provided a comprehensive understanding of the dataset's elements and their global implications. The findings illuminated intricate interplays between soil types, ecosystem services, protected areas, and road networks, with the potential to inform various domains, including environmental management, infrastructure planning, and ecological research.
+
+### Actionable Key Points
+
+- Prioritize data cleaning and validation processes to resolve geometry issues and enhance the accuracy of geospatial datasets.
+- Encourage comprehensive reporting and the establishment of ownership structures for protected areas to facilitate better management.
+- Invest in the classification and reporting of road types to support improved infrastructure planning and development.
+- Consider the distinct ecological roles of different soil types and their contributions to ecosystem services when formulating conservation and land management strategies.
+- Acknowledge the significance of waterbodies and glaciers, which, although not terrestrial soil resources, play crucial roles in the Earth's ecosystem, particularly in the context of climate change.
+
+### References
+
+[Organic Soils](https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/organic-soils)
+
+[Quantifying the Ecosystem Services of Glaciers Highlights Their Importance to Humankind](https://news.climate.columbia.edu/2021/09/17/quantifying-the-ecosystem-services-of-glaciers-highlights-their-importance-to-humankind/#:~:text=The%20benefits%20detailed%20in%20the,aspects%20of%20glaciers%2C%20albeit%20briefly.)
+
+[Glaciers Ecosystem](https://www.antarcticglaciers.org/glacier-processes/glacier-ecosystems/#:~:text=Indeed%2C%20since%20glaciers%20and%20ice,form%20a%20distinct%20biome3.)
+
+[Acquatic Ecosystems](https://joint-research-centre.ec.europa.eu/jrc-news-and-updates/aquatic-ecosystems-good-conditions-yield-better-services-2019-04-11_en#:~:text=Importance%20of%20aquatic%20ecosystem%20services&text=These%20include%20water%20provisioning%20(supply,against%20the%20sea)%20and%20recreation.)
+
+[Major Soil Resources of The World](https://www.isric.org/sites/default/files/major_soils_of_the_world/set9/ab/albeluvi.pdf)
+
+[World Soil Resources- FAO](https://www.fao.org/3/i5199e/i5199e.pdf)
+
+[Soil Classification System](https://www.eolss.net/sample-chapters/c19/e1-05-07-11.pdf)
+
+[Reference Base for Soil Resources](https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/world-reference-base-for-soil-resources)
+
+[HAC Soil Classification - FAO](https://www.fao.org/3/j2132s/J2132S22.htm)
+
+[Global Roads Documentation](https://sedac.ciesin.columbia.edu/downloads/docs/groads/groads-v1-documentation.pdf)
+

Outreachy_Nwajiunor_2023/Task 5/User documentation.md

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+# User Documentation
+
+Effective land sector management plays a crucial role in ensuring sustainable agriculture, biodiversity conservation, and overall environmental quality. This user documentation provides a comprehensive guide on how to work with the Land Sector Dataset repository for in-depth data analysis. The documentation includes an overview of the tasks, tools used, and key insights derived from the analysis.
+
+## Table of Contents
+
+1. Getting Started
+2. SDGs Alignment/ Mapping
+3. Geospatial Analysis
+4. Data Visualization
+5. Results
+6. FAQs
+7. Conclusion
+
+### 1. Getting Started
+
+**Objective**
+The primary goal of this project was to analyze the Land Sector Dataset repository. This repository contains data related to administrative, biological and ecological, soil, land cover and climate. The project aimed to extract meaningful insights, spatial patterns and relationships from these datasets. 
+
+**Prerequisites**
+Before proceeding, it is assumed that you would have met some conditions:
+
+a. Basic understanding of geospatial data and the concepts of SDGs. 
+
+b. You will also need a performant desktop machine or laptop with a minimum storage of 128GB and 8GB RAM  is required for pre-processing global open-source datasets, as spatial datasets can be memory-intensive.
+
+**Datasets**
+- Administrative
+- Biodiveersity, AgroClimatic and Ecological Zones
+- Land Cover
+- Soil 
+
+### 2. SDGs Alignment/Mapping
+Datasets are matched with relevant SDGs to identify goals related to land sector data, including land use, environmental impact, and social implications.
+
+### 3. Geospatial Analysis
+
+Focused on global patterns, specifically examining the interplay between soil types, ecosystem services, protected areas, and road networks on a global scale. These insights have the potential to inform diverse domains, encompassing environmental management, infrastructure planning, and ecological research.
+
+### 4. Data Visualization
+
+The visualization tools provide valuable insights into the alignment between various datasets and the Sustainable Development Goals (SDGs). Here's how you can effectively use these tools:
+
+Exploring Unassigned Entries: The visual representations reveal that a substantial number of entries (188,415) remain unassigned to specific SDGs. Users can delve into these entries, particularly those categorized as "unspecified" or "contested" based on the "Ownership Structure" column within the "Protected Areas" dataset. This exploration can help uncover hidden information and assist in SDG mapping.
+
+Focusing on Specific SDGs: Users can filter the visualizations to focus on a particular SDG of interest. For example, if they want to understand how road types align with SDG 11: Sustainable Cities & Communities, they can use the visualization tools to explore these connections in detail.
+
+Identifying Spatial Overlaps: The red areas on the map represent the intersection of the Mapped SDG Roads and Mapped SDG World Resources. Users can study these regions to understand where these datasets spatially overlap and how they are interconnected.
+
+Gaining Insights: Users can draw meaningful insights from the visual representations, such as understanding the alignment of road types with specific SDGs. This information can be valuable for research, decision-making, and policy development.
+
+### 5. Results
+- The clear mapping of soil resources to SDG 15 underscores the significance of these resources in achieving the SDG's objectives, particularly related to terrestrial ecosystem conservation.
+
+- The alignment of road types with SDG 11 emphasizes the role of infrastructure in creating sustainable and resilient urban environments.
+
+- Spatial intersections pinpoint areas where mapped SDG Roads coincide with world resources, providing opportunities for in-depth analysis of resource accessibility and infrastructure development.
+
+- The presence of 188,415 unassigned entries in the "Protected Areas" dataset underscores the need for further data categorization, likely driven by issues such as "unspecified" or "contested" classifications.
+
+- The majority of mapped entries (51,686) aligned with SDG 15, highlighting a strong focus on the conservation and sustainable management of terrestrial ecosystems within the "Protected Areas" dataset.
+
+### 6. FAQs
+
+Q1. Who can use this documentation?
+
+A. This is designed for researchers, policymakers, analysts, and anyone interested in exploring the impact of land attributes on sustainability goals.
+
+Q2. What do I need to get started?
+
+A. To get started, you will need;
+
+- Basic understanding of geospatial data and the concepts of SDGs. 
+- You need a desktop or laptop with a minimum storage of 128GB and 8GB RAM  is required for pre-processing global open-source datasets. 
+-  Python installed on your system
+- An internet connection is required for data retrieval.
+
+Q3. How do I install Python on my system?
+
+A. You can download and install Python by following the official Python installation guide. Visit the Python website at [python.org](https://www.python.org/)  
+
+Q4. Do I need to install the GeoPandas library?
+
+A. Yes, the Land Sector Data utilizes geospatial analysis and mapping features, which require the GeoPandas library. To install the GeoPandas library, use this command `pip install geopandas` in the terminal or console. 
+
+Q5. What kind of data would I work with?
+
+A. You would be working with various datasets related to land use, environmental impact, and social implications, all aligned with specific SDGs.
+
+Q6. Is this an open source project?
+
+A: Yes, this is an open source project. It means that the source code of the software is freely available, and anyone can view, modify, and distribute it according to the terms of its open source license. This openness encourages collaboration, transparency, and the community's active participation in its development.
+
+Q7. Can I explore specific attributes in the data?
+
+A. Yes, you can select specific attributes within the datasets to analyze and visualize their relationship with SDGs.
+
+**Contact Information:** For all inquiries, feedback, or technical support, the support team is readily available to assist you. Please feel free to contact via [email protected]
+
+### 7. Conclusion
+
+This document is a complete guide for understanding integrated land sector data and how to use visualization tools. It helps users in land management, conservation, and following global SDG goals. With the provided data, tools, and interactive prototype, users can make well-informed decisions in land management and sustainable development, all aligned with the SDGs.