A mixed-method approach to solid waste mapping in Mogadishu

Community Development/Environment/OpenStreetMap/Public Services/Spatial Collective/Waste Management

A mixed-method approach to solid waste mapping in Mogadishu

Posted on March 22, 2023 by Primus / 0 Comment

Last year, we collaborated with Humanitarian OpenStreetMap Team and OSM Somalia to generate high-quality geographic data aimed at comprehending the extent and dispersion of solid waste sites in Mogadishu.

Managing solid waste is a multifaceted and intricate problem that necessitates a thorough comprehension of the ecosystem, involving various actors and factors such as social, economic, governance, environmental, cultural, and technological processes. Therefore, we carried out a mixed-method approach comprising a combination of quantitative and qualitative data collection methods to capture all pertinent data.

The digitization of satellite imagery played a pivotal role in this approach, providing a base layer for all other datasets. All buildings in Mogadishu were digitized. The digitized buildings, coupled with satellite imagery, served as a foundation for Focus Group Discussions (FGDs) held with representatives of 17 districts in Mogadishu. These FGDs enabled the identification of people’s perceptions, concerns, and ideas in a spatial context. The resulting data was used to develop detailed maps pinpointing areas that necessitate attention and intervention. The FGDs were complemented by Key Informant Interviews (KIIs) that provided valuable insights into the waste management ecosystem in Mogadishu. KIIs gathered top-down perceptions from formal governance actors, while FGDs captured the opinions and experiences of both formal and informal governance actors such as local government officials, community leaders, citizens, and even garbage pickers. This comprehensive approach allowed for a better understanding of the issue, and the resulting data can be used to develop effective policies and strategies that take into account the needs and experiences of all stakeholders.

*Waste management providers and activities in Mogadishu gathered through the Focus Group Discussions*

Data verification was carried out through field visits and mobile data collection to ensure that the data collected was accurate and dependable. This validation ensured that the data collected through KIIs and FGDs, and the resulting analysis and maps, were based on trustworthy data.

Finally, all the data were merged for further analysis and map creation. The resulting maps and analysis provide a comprehensive understanding of the waste management ecosystem in Mogadishu and can be utilized to develop targeted policies and strategies that address the specific needs and challenges of the city.

In summary, the mixed-method approach adopted for mapping waste in Mogadishu provided a comprehensive and detailed understanding of the issue, and the resulting data can be used to develop effective policies and strategies that enhance waste management practices in the city.

Finally, hats off to the OSM Somalia members who carried out the fieldwork, sometimes under very challenging conditions! Their dedication is truly commendable.

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Community Land/Economic Development/Environment/Land/Property Rights/Spatial Collective/Unmanned Aerial Vehicle

Secure Tenure on Zanzibar

Posted on March 21, 2023 by Primus / 0 Comment

Using cutting-edge technologies to simplify the process of obtaining proof of property ownership in Zanzibar

Our solution is designed to streamline and modernize the existing paper-based data collection processes and parcel mapping methodologies, while also addressing the limited professional human capacity and high unit costs of land data collection. Working in partnership with the Commission for Lands and leveraging modern technology, including drone imagery, digital tools, and cloud computing, we have developed a streamlined process that can issue land certificates in months rather than years. Our approach consists of several components, each of which was developed to tackle a specific challenge.

First, we digitized the data collection processes, moving from paper-based methods to digital methods. This allowed us to improve data capture, enhance data security, and eliminate the existing problem of loss of paper records. By using digital methods, we were able to collect and store land data more efficiently and effectively, ensuring that it was accessible and secure.

Second, we set up a fit-for-purpose parcel mapping component that utilized high-resolution aerial imagery from drones and tablets’ in-built geolocation capabilities. This cost-effective solution delivered sub-meter mapping accuracy that was legally required for parcel demarcation. By using drones and tablets, we were able to produce accurate and reliable parcel maps more quickly and at a lower cost than traditional methods.

With the help of the Cadasta Foundation and customized ESRI‘s ArcGIS Survey 123, we completed the technical setup and consolidated the digital data collection methodology and the parcel mapping component into one simplified data collection tool. This tablet-based software enables in-situ capture of parcel boundary and landowner’s bio-data at a fraction of the time and cost previously required. By simplifying the data collection process, we were able to reduce the time and cost required to collect land data, making it more accessible to landowners and other stakeholders.

Using digital tools to document land rights

For data collection, we relied on the young tech-savvy communities in Zanzibar, by training a dozen youths in using the developed tool. We also built the capacity of existing surveyors to manage the trained youth, effectively solving the human capacity challenges by enabling a large pool of workers to be deployed and speeding up the data collection process. By engaging local communities and building local capacity, we created a sustainable solution that empowered the people of Zanzibar to take ownership of the land adjudication process.

Finally, we made the adjudication process more straightforward and cost-effective for the landowners by collecting all the required information in the comfort of their homes. This door-to-door approach saved time and money for the landowners who previously had to travel to and from the land adjudication offices to submit various land documents. This approach encouraged the participation of previously marginalized landowners and simplified the adjudication process for everyone involved.

Our digital data collection solution has shown significant improvements compared to traditional methods. The old method required at least 24 months, including legally mandated waiting periods, to collect data for land adjudication. However, our solution managed to document over 1000 land parcels and issued more than 100 government-approved land titles in only a few months. This demonstrated the potential to produce land titles at scale and in a significantly shorter time frame and at a reduced cost. As a result, our solution has received support from various stakeholders, including the government, survey professionals, and landowners, who view it as a proactive and efficient approach to land documentation.

Citizens receiving Certificates of Occupancy

We believe that our solution has the potential to transform land adjudication in Zanzibar and improve access to property rights for its citizens.

Additional information about the initiative can be found here:

https://news.trust.org/item/20220726100224-q05uk

https://www.reuters.com/article/tanzania-housing-tech-idUSKBN2841O4

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Community Land/Land/Property Rights/Spatial Collective

Consensus in Documenting Land Rights

Posted on January 26, 2023 by Primus / 0 Comment

There has been a growing focus on the importance of consensus when it comes to determining land rights. This is particularly true when it comes to the collection of data on land properties and the demarcation of boundaries.

In recent years, our team has spent a significant amount of time working on testing and developing new technologies for land rights, with a focus on improving the traditional methods of collecting data on land properties. We have conducted several comprehensive studies in Kenya, including in Tana River County where we helped communities map their ancestral and communal land, and in Taita Hills County where we tested and modified new technologies for land demarcation.

One of the most significant projects we have undertaken is in Zanzibar, an archipelago off the coast of Tanzania. In Zanzibar, the majority of land properties are not documented and, until recently, the number of built properties was unknown. Through our efforts, we were able to map all the buildings on the archipelago and assign each one a unique ID.

In collaboration with the Zanzibar Commission for Lands, we aimed to modernize the process of land adjudication. We identified that the traditional methods were outdated and that the collection of data and mapping of boundaries were not seamlessly integrated. These outdated methods also relied heavily on the availability of professional surveyors, which was scarce, and on the time of adjudication officers, which was limited.

Instead of relying on the limited availability of professionals, we decided to empower the community by providing them with tools to collect their own data on land properties, within the bounds of the law. By involving the community, and utilizing new technologies such as drone imagery, tablet-based survey forms, and cloud computing, we were able to streamline and speed up the process. The community was actively engaged in gathering and agreeing on the boundaries, resulting in increased accuracy through mutual agreements among neighbors. Finally, the whole process was overseen by the adjudication officers from the Commission for Lands, providing it legitimacy. This highlights the significance of building consensus in determining land rights.

When the project was completed in 2022, a total of 1000 land properties were documented. The process of documenting these properties was greatly streamlined by the active participation of community members. At this moment, over 100 community members were already able to obtain government-approved certificates of occupancy.

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GIS/Micro-tasking/Platform Development/Spatial Collective/Terrestrial Imagery

Consensus in Mapping

Posted on January 18, 2023 by Primus / 0 Comment

In this piece, I will specifically talk about community-led field mapping and how terrestrial imagery and consensus can be used to improve the accuracy of data.

I explain mapping as a method to determine where things are located in space and time. For example, a house is located somewhere in space and time and so is a conversation between two people. Both can be documented or mapped in a similar way.

Traditionally, we rely on professionals to record places and events and present them to us in various ways, usually through data visualizations or maps. Professionals have the expertise, use highly technical tools in their craft, and abide by rules and standards. Their reputation and work license is on the line.

It goes without saying that having access to accurate information is essential not only in the realm of geospatial sciences but life in general. Having accurate data enables us to make the right decision at the right time, it allows us to understand the world and its complexities better.

In recent years, community mapping initiatives exploded worldwide. The cost of technology to collect and display data has reduced significantly and so has the skill necessary to use this technology. Hundreds of community-led initiatives are underway each year where oftentimes inexperienced data collectors produce much-needed information for all sorts of purposes.

These initiatives are essential to fill in the gap of missing data, especially in places that are not well documented. They take it upon themselves to supply accurate and relevant information or knowledge about a place.

Community-led field mapping carried out by Spatial Collective

But how do we ensure that the data they collect is accurate? The repercussions for misrepresenting a place are much lower for a community mapper than the professional surveyor if there are any at all. Leaving out a location or two or even fabricating information isn’t necessarily penalized.

Community-led field mapping relies on the trust of individuals to do a good enough job. This is because verifying field data is difficult. By difficult, I mean repeating an exercise by walking to every place and ensuring that both location and attribute information is correct is time-consuming. The amount of information that community mapping initiatives produce is often too big for this type of on-the-ground review, and revisiting sites over and over again is too expensive.

Furthermore, these initiatives rely heavily on resource mobilization and funding usually only covers one data collection cycle. When the funding runs out, so does community mapping in most instances. The areas that were underserved before become underserved again and the data can quickly become unreliable.

We thought a lot about how we can improve field data collection. We asked ourselves: Is there a better way to utilize the power of the community to collect data and keep the information more current, less resource-dependent, more accurate, and easier to update and verify?

A solution we tested that seems to work well is building a synergy between terrestrial imagery and building consensus through micro-tasking.

Terrestrial imagery refers to photographs or videos of the Earth’s surface taken from the ground or from low-altitude aircraft. These images can be captured using a variety of techniques and technologies.

As cartographers, we are particularly interested in the location where the image was captured and the information depicted in it, as the imagery can provide a wealth of useful data.

The most efficient method for obtaining that data from those images is through micro-tasking. Micro-tasking refers to the process of breaking down a larger task into smaller, manageable tasks that can be completed by individuals or a group of people, usually via the internet. A micro-tasking campaign involves distributing terrestrial imagery to a large number of individuals for the purpose of labeling those images. In this way, thousands of images, and their locations, can be reviewed daily.

The individuals involved in micro-tasking build consensus on every image about what is depicted in an image. In the context of terrestrial imagery, consensus can be understood as the methodology of achieving a mutual agreement on the information depicted in an image and its appropriate representation.

This methodology allows us to scan each area for new information monthly if needed at a relatively low cost, making the data more accurate. The implementation can be carried out by a few people who are needed to manage the cameras and walk the areas of interest, while the bulk of the work is done by the individuals from the comfort of their homes.

The main benefits of using terrestrial imagery and micro-tasking are the speed with which it can be rolled out, the cost associated with it, and the involvement of a larger community to decide what data is depicted in an image – and by the association at a location -, and how it should be presented.

In summary, field data collection is essential, especially in poorly represented places. However, fieldwork is expensive because it requires a lot of manpower to carry out, and the cost is oftentimes prohibitive for additional on-the-ground field data validation. Terrestrial imagery and micro-tasking can significantly contribute to the speed with which the data is collected. At the same time, micro-tasking enables building consensus through the engagement of people who collectively decide what is represented at each location, making the data more accurate.

The world is rapidly changing and the need for the most current and accurate information is increasing. It goes without saying that the methods we use to document this rapid change must follow the trend and evolve or they will falter.

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Community Development/Data/Economic Development/Spatial Collective

Kenya Digital Public Works

Posted on November 30, 2022 by Primus / 0 Comment

Between 2021 and 2022, we carried out a project called Kenya Digital Public Works. Here’s a short description of the project with more on the way in the future.

The goal of the Digital Public Works project was to produce the information necessary for informal settlement upgrading by engaging with and providing short-term employment opportunities to urban youth through data collection.

The project was carried out in collaboration between Nairobi County, the World Bank, the State Department of Housing and Urban Development, the project implementing partner Spatial Collective, and the three communities in Nairobi: Embakasi Sokoni, KCC Settlement, and Kahawa Soweto.

To an extent, the project drew inspiration from the Kazi Mtaani initiative, an initiative aimed at empowering youth and providing them with a source of income mainly through the beautification and sanitation of the city’s public spaces.

The DPW retained the youth component similar to Kazi Mtaani but engaged them in digital work instead of physical activities. The youth, instead of working on beautifying community gardens, learned about the digitization of aerial imagery; instead of creating and paving walkways, they used terrestrial cameras for image acquisition; and instead of repairing and refurbishing public spaces, they carried out digital micro-tasking and household surveys.

The project further implemented the concepts of community data ownership and localization of knowledge and took advantage of the proliferation of new and affordable technologies. Instead of relying on private companies to carry out the work, DPW recruited and trained the youth from the settlements and gave them tools to collect their own data.

Youth participating in Digital Public Works

Apart from providing short-term employment opportunities to the youth, the project had to satisfy the data needs of the Kenya Informal Settlements Improvement Project (KISIP). These were thematically organized as data for investment selection, disaster risk management, solid waste management, socio-economic inclusion, and crime and violence.

DPW set out to answer a question: Can the youth use affordable and widely available technologies to gather the information necessary to support informal settlement upgrading?

Each of the thematic areas mentioned above had unique data requirements. For this reason, Spatial Collective developed several data collection modules consisting of digitization of aerial imagery, mobile data collection, acquisition of terrestrial imagery using 360-degree cameras, micro-tasking, and household surveys.

The project recruited, trained, and employed 300 youth from the three informal settlements to collect data, while at the same time monitoring their progress, and paying them for the work done.

The project specifically targeted youth because they represent the majority of the population and are among the most vulnerable groups due to the lack of opportunities, especially in urban centers.

The applications for work were made open so anyone living in the three settlements aged between 18 and 35 could apply and the selection criteria were as inclusive as possible. In the end, out of 300 youth, 70% were women, 10% were persons with disabilities, and they came from all walks of life, religion, education, and income levels.

Once selected, the youths were placed in the data collection modules to receive orientation and training and start work. Each individual, each day received a number of predetermined tasks depending on which module they were placed in. For example, the digitizers had to digitize 200 buildings per day, the mapping team had to collect data on 30 points of interest, micro-taskers had to tag 300 images, and the survey team had to carry out 10 household surveys in a day. Each of these tasks took approximately the same amount of time to complete to make the work more equitable.

At the end of the day, they submitted their work for evaluation by experienced validators who checked the quality of the data and estimated their daily payments.

The payments were divided into three categories: base pay, quality, and overtime. Each youth received an equivalent to the daily minimum wage for all completed tasks in a day. But the youth who produced good quality work earned extra cash and qualified for overtime which earned them another level of payment on top of that.

The project used incentives like these because it was found to be the best way to ensure that the quality of work satisfied the government’s data requirements.

At the end of a four-month-long exercise, the youth collectively spent thousands of hours on digital tasks, producing the most detailed dataset on the three settlements ever created. They performed 1,8 million digital tasks, digitized 350,000 buildings, collected thousands of points of interest, gathered 6,500 terrestrial imagery, produced 1,5 million tags on that imagery, and carried out 700 household surveys, providing essential information for the Kenya Informal Settlement Improvement Project and earning money in the process.

Data on buildings from the three settlements

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Data/Qualitative Data/Reflections/Spatial Collective

Thoughts on Analyzing and Visualizing Text Messages

Posted on October 13, 2022 by Primus / 0 Comment

Nairobi was shut down during the peak of the pandemic in 2020. The city was closed off from the outside world and a curfew was imposed, limiting movement within. Everyone had experienced this lockdown bogged down in their own estate or community.

During this time, we deployed an application called Mtaa, a mobile application that enables users to send geolocated text messages with an “emotion” attached to them. We deployed the app to keep in touch with our friends and team members and to collect data on people’s experiences of the pandemic and the measures imposed.

Our friends sent more than 700 messages in a period of only a few weeks. The messages ranged from day-to-day interactions, reports of extreme kindness and sacrifice, to small acts of daily life like painting graffiti and making music videos, to talking about crime and lack of essential services, such as access to water and food. The app gave us a sense of purpose during trying times, but most importantly, it kept us close and connected through the sharing of experiences. The exercise also gave us an opportunity to see whether we can make these narratives into actionable data.

Analyzing more than 700 messages posted in several languages represented a unique challenge. There are a few standard ways to analyze such data, either geospatially or statistically, each with its own strengths and shortcomings. I’ll touch on a few in this blog post.

I’ll start with the most obvious and easiest one: “putting points on the map”. Each message is geolocated, so the most straightforward way is to display them on a map. Points on the map are visually appealing but not particularly useful, especially when points start to cluster in the same area. Once the number of data increases, the map itself becomes crowded and hard to read.

Text messages sent from Mlango Kubwa, Nairobi

Second, our messaging platform allows people to express their ‘feelings’ about a situation in form of emotions. Users can tag each message based on whether they think it has a more positive or negative connotation associated with it. These so-called ‘feelings’ can be displayed as an aggregate in an area and represented as such. We used hexagons to represent an ‘average emotion’ associated with an area (see the image below). In this way, we can identify areas that have more positive or negative opinions associated with them. However, by displaying opinions as a ‘vibe’ we lose the granularity or detail that makes these opinions so interesting in the first place.

Hexagons represent an ‘average emotion’ associated with an area

Third, we can tag each message based on the topic it depicts. For example, if a message talks about water, we tag it as ‘water,’ if it talks about crime, we tag it as ‘crime,’ etc. To do this we have to read through all of the messages, create categories, and manually place each message into a relevant category. Naturally, this is time-consuming but it allows us to look at the statistical and spatial distribution of topics. For example, we can see how many messages there are about the lack of food, security, development, access to services, or even people having a good time, and where they are located. This process could be sped up using language processing techniques but they would have to work on several languages at once. Tagging messages in this way does have its merit in that it allows for easier analysis, however, as in the previous point, we lose the detail and importance of each message as a unique story.

Chart representing topics of text messages

Further, we can experiment with turning people’s experiences into more traditional, social-media-driven narratives by merging visuals with messages. This is a very powerful storytelling technique fit for modern-day social media consumption (see image below), but apart from being visually striking, there’s not a lot there. Plus, it adds human interference through selecting and preparing each ‘experience,’ which interferes with the free-flowing communication about a place that people occupy.

Finally, we can display messages on a timeline. This looks cool but is only useful if we’re interested in the temporal distribution of certain events at a certain location. We can see in the image below that May 8 was a particularly dark day in our collective family.

I’m sure there are more ways of analyzing qualitative data in the form of text messages. However one goes about it, it is important to note that peoples’ narratives and stories are essential in learning about a place. Telling a story through data needs to be a multilayered process, it has to rely on more than just ‘points on the map’ or raw statistics. We learn the most when we listen with curiosity and when we listen to understand.

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Community Development/Mapping/Training

Nungwi, Chwaka, and Makunduchi Mapping

Posted on August 15, 2022 by Primus / 0 Comment

In 2020 and 2021, Spatial Collective provided mapping services for Zanzibar’s Nungwi, Chwaka, and Makunduchi settlements. The project fell under the broad framework of the Tanzania Urban Resilience Program and was meant to showcase how locally accessible, low-cost technologies can support resilience building and urban development planning by producing high-quality spatial information. Specifically, the assignment was meant to build the capacity of university students through an industrial training program and generate up-to-date spatial information to support urban planning in Nungwi, Chwaka, and Makunduchi.

On two separate occasions in 2020 and 2021, ninety students from the State University of Zanzibar participated in an eight-week-long industrial training program. During this period, the students learned about the theoretical and practical aspects of community mapping, including a wide range of soft skills such as communication and community management which are required in a realistic work setting.

In Nunwgi, using smartphones, handheld GPS devices, and high-resolution drone imagery, the students mapped over 600 businesses, 465 amenities, 4,000 trees, and over 38 km of roads. To update and improve the quality of the existing building dataset in Nungwi, they manually added 500 buildings to the digitized dataset of about 4,800, and also captured 62 tourism-related facilities, 99 restaurants, including entertainment areas, and 47 craft workshops. In the end, working with local historians in the area the students mapped 23 places of cultural significance.

Similarly, in Chwaka and Makunduchi, using the same technology and approach, the students mapped over 300 businesses, 500 amenities, 884 electrical infrastructure features, and over 50 km of roads. To update and improve the quality of the existing building dataset in Chwaka and Makunduchi, they added building attributes to over 7,500 buildings and captured 846 additional buildings.

During the program, the students gained fundamental knowledge in setting up mapping projects. At the same time, the datasets produced will benefit the Zanzibar Urban Services Project, the Department of Urban and Regional Planning, and other stakeholders as they undertake various urban improvement initiatives in the three areas.

Finally, the project showcased how the potential of innovative technologies paired with the local capacity can provide stakeholders with timely and accurate information.

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Community Development/Spatial Collective/Training

Community Mapping Urban Risks in Mwanza

Posted on June 16, 2022 by Primus / 0 Comment

In late 2020 and early 2021, Spatial Collective (SC) carried out the Community Mapping of Urban Risks in Mwanza under the broad framework of the Tanzania Urban Resilience Program (TURP). To complete the project, the company partnered with the Humanitarian OpenStreetMap Team (HOT) and OpenMap Development Tanzania (OMDTZ). This assignment intended to showcase how locally accessible, low-cost technologies can support resilience building and urban development planning through the production of high-quality spatial information. Specifically, the assignment’s goal was to train university students and government authorities in community mapping by coordinating several community mapping engagements in pre-selected wards in Mwanza and producing up-to-date, open, and accurate data on exposure to floods and rockfalls.

Seventy-nine students from the Institute of Rural Development Planning (IRDP) and the Saint Augustine University of Tanzania (SAUT) participated in a two-month-long industrial training program. During this period, they learned about the theoretical and practical aspects of community mapping. By putting theory to practice, they, together with hundreds of community members, collected a series of disaster-related data touching on flood-prone areas, historical rockfall incidents, urban exposure, and drainage infrastructure. The work focused on two municipalities: Nyamagana and Ilemela.

Using a mixed-method approach which consisted of digitizing the satellite imagery, mobile and GPS field data collection, community consultations, and stakeholder meetings, the students collected more than 300,000 buildings using satellite imagery, 15,000 locations of flood-prone areas, 800 locations exposed to rockfalls, and more than 80,000 points on urban exposure. In addition, more than 1,500 drain segments with 177 km of drainage lines, 3,113 drainage-related points, and 1,328 elevation points were mapped using a combination of mobile phones and Do It Yourself Real-Time Kinematic (DIY RTK) GPS.

After several months of fieldwork, the students gained fundamental knowledge in setting up community mapping projects and producing datasets that benefit Mwanza’s local authorities and other stakeholders in infrastructure improvement projects. Finally, the project highlighted the potential of pairing innovative technologies with local capacity to provide stakeholders with timely and accurate information.

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COVID-19/Mapping/Mtaa/Spatial Collective

Mtaa and COVID-19

Posted on May 26, 2020 by Primus / 0 Comment

Informal settlements are often missing from the geographic and statistical representation of countries. Nairobi’s informal settlements are no exception. Very little information is available on the quality and quantity of public institutions and amenities, public services, or on the population itself living in the areas. They are often not even represented on official maps.

This invisibility became even more pronounced with the onset of Covid-19 crisis when movement in and around Nairobi, and Kenya, was significantly limited. This lack of free movement introduced yet another problem: due to the travel restrictions, the information flow from these areas also got restricted to an extent.

Social media, such as WhatsApp, Facebook, and Twitter filled in the gap of missing information but, while these tools do a great job of enabling easier public sharing, the information itself remains scattered through the interest groups. If you’re not a part of the group, you simply miss out.

In order to understand what our friends and co-workers, their families, and communities are going through, we needed to consolidate all the information in one spot in an easy, accessible way.

***

Mtaa is an application we developed to conduct a quick scan of the area where we plan to work. Users send texts, together with a location and an “emotion” attached to the location. Everyone is free to send whatever message they wish. The messages are open, without censorship or rules of what should be posted. We keep it this way because at the moment we rely on trusted sources for information and we don’t see the need to censor anything. We love such qualitative data because we love stories and stories of what is going on in informal settlements are often lacking.

Then, the pandemic hit.

***

As a company focused on community data collection, we had to find a way to support our colleagues, enable safe data collection, and still center community experiences.

Mtaa enabled us to do so.

Our friends utilize the platform to send messages – safely from their homes – about experiences they and their communities are facing. These friends are trusted reporters, many of whom have worked with or been trained by us before, sharing experiences of the neighborhoods that are otherwise often missing from representation.

Currently, they’ve sent about 500 messages from Mathare, Kibera, Kariobangi, Kawangware, City Centre, Ngong Road, Mukuru, and Umoja neighborhoods in Nairobi. The messages range from day-to-day interactions, reports of extreme kindness and sacrifice, small acts of daily life like painting graffiti and making of music videos, to talking about crime and lack of essential services, such as access to water and food.

Water situation is very dire here. We have gone so long without water services and where one gets some, the community scrambles and struggles with high cost and long queues in order to access the commodity.

Thievery activities taking place due to lack of finaces and very limited job opportunities. Especially now it is really bad along the roads.

Hii Covid imekuja sana waaaaah!!!

Woke up, all good! Good morning Mlango!

We must emphasize that no one is asked to, nor needs to, go and collect data outside the safety of their homes. The only rule is that they send whatever they want whenever they want it: rumors, feelings, and other relevant messages as and when they see fit.

We are now working on various analyses and visualizations of data to identify hot-spots, priority areas, and main issues in each community based on this incoming information. One of the visualizations – an interactive map of messages received and their locations – can be seen below. Now, our job is to analyze and share the information with relevant actors providing services on the ground. In the end, the goal is to make this information useful.

Geolocated messages from Mlango Kubwa, Mathare

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Data/GIS/Household Survey/Mapping/Resilience/Spatial Collective/Survey/Training

Household Survey

Posted on January 17, 2020 by Primus / 0 Comment

This is part of a series on the Industrial Training of Students on Zanzibar by Spatial Collective. You can read parts one, two, three, four, five, and six here.

One of the topics covered during the training was on using mobile phones to collect data on households. The goal was to introduce the students to mobile data collection and to teach them how to interact with community members while conducting a survey.

KOBO software was used for data collection and some of the data collected were:

building type, material, structure, roof, building levels, condition, and age
how many people – adults and children – live in the household
does the household have a drainage connection
does the household have a sanitation connection
does the household have an electricity
does the household have a water connection
how does the household get rid of the waste
has the community experienced flooding recently
has the household experience flooding recently
what were the main causes of flooding

The survey was carried out in one of the most flood-affected areas of Zanzibar Urban West. A few visualizations of the 2,300 households surveyed are displayed below.

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