Sub-Saharan Africa is one of the least urbanized regions in the world, yet it is expected to experience the highest rate of urban population growth in the coming decades.
In a context of widespread poverty, climate change and limited capacity to manage the rapid growth of urban population, urban growth comes with substantial costs. Cities in Sub-Saharan Africa are increasingly affected by disasters and hazards, and large urban centres are facing challenges such as overcrowding, environmental pollution and depletion of resources.
Decision and policy makers in the region need dependable and up to date information on urban growth, disaster impact and risk prediction in order to plan how to best use resources and make informed decisions. In this framework, mapping and remote sensing technologies are playing a crucial role to foster sustainable development and to address the effectively address the demanding tasks this region is facing today.
Cloud based imagery service for land management in Uganda
The rapid population growth, the increasing demand for land – both for settlement and for agriculture – and the industrial developments are driving land degradation including wetland changes in Kampala. In addition, the significant pressure on land deriving from human activities is complicated by the current complex land ownership patterns that exist in Uganda
today.
The Country is certainly facing several challenges encompassing a decentralisation of land management, scattered local and central institutions and, most importantly, a manual cadastral system of land administration difficult to keep up to date with consistent information. All these factors affect the growth of ownership’s demands of land in wetlands which many people claim through titles.
Elaborating a comprehensive and reliable land administration system for the entire country is a prerequisite to boost sustainable urban development and protect wetlands. A transparent and efficient land management system would also help to mitigate the current difficult processes associated with obtaining and transferring evidence of land ownership as well as generating a more attractive environment for investment.
Providing Very High Resolution (VHR) imagery with submeter spatial resolution of large regions through and updating them on a timely manner is crucial to create the foundational layers of a land and cadastral system with fresh and detailed information such as seamless mosaics of nations and wall-to-wall coverages
In particular, VHR imagery can be used to identify small-scale changes and heterogeneous urban structures, enabling a highly detailed analysis of the urban morphology, including the detection of single houses and infrastructure networks.
Fig. 1. Change detection imagery service on 2015 (left) and 2018 (right) over Kampala, Uganda, showing new houses and facilities near the wetlands area
Cloud-based imagery is crucial for this purpose. It can be accessed through an imagery service easy to integrate in the GIS tools of local institutions and agencies without requiring large disk storage, especially needed when performing time series analysis. Delivering the data through an imagery service enables all users to access timely, reliable and quality assured imagery directly into their applications and desktops. Hosted in Amazon Web Services using ESRI ArcGIS technology, all the imagery is optimized for the cloud and orthorectified on-the-fly using accurate DEMs. Users can utilize the multi-temporal VHR imagery service and start building valuable apps for monitoring, change detection and precision insights including land cadastres layers at scale. These valuable Earth Observation (EO) cloud-based imagery service provides the foundational product easy to plug-in into preferred GIS software packages used by land administration and cadastre agencies. In addition, the cloud-based imagery service compliments and incorporates multi thematic information sources such as legacy cadastre records.
Monitoring and preserving natural resources
The drainage of wetlands, together with inadequate provision of sanitation services to the residents of Kampala, are having further consequences and resulting in an increased pollution of water sources. This decline in water quality has implications on human health and on the economy as maintaining the quality of water has required ever increasing chemical inputs into the water treatment plants with the subsequent cost implications.
The Lake Victoria Inner Murchison Bay is one of the bays getting polluted due to human activity. The polluted surface water should be subjected to natural purification by the plants and microbes contained in the wetlands, but that is not occurring efficiently because of the large scale draining that has been ongoing over recent years. Wetlands can only be effective bio-filters under conditions of low nutrient loading and abundant swamp. Environmental monitoring and change detection are crucial to prevent a degradation of resources and public health issues. An analysis performed over imagery captured in 2015 and 2018 shows the enormous change that Murchison Bay has undergone during the last years. Wetlands loss and degradation is perfectly visible in the NIR (Near Infrared) images (Figure 1). The varying shades of red across the NIR images indicate how sensitive the satellite’s multispectral camera is to differences in vegetation cover and chlorophyll content. This is used to provide key information on plant health. Brighter reds indicate more photosynthetically active vegetation.
Fig 2. Cloud-based submetric Change Detection service using False Colours imagery (R.G,NIR) showing changes on wetlands between 2015 (left) and 2018 (right) highlighted in the yellow box. All the processing is on-the-fly.
We continued our analysis applying an NDVI (Normalized Difference Vegetation Index) analysis calculated on-the-fly over the sub-metric cloud-based imagery service, which is very useful to differentiate changes in vegetation. Figure 3 shows differences in the NDVI in the Lake Victoria Inner Murchison Bay between 2015 and 2018. Different values ranging from +1.0, to -1.0 are represented in these NDVI imagery. High levels of NDVI are represented in the green and yellow shades, while low NDVI values are pictured in the grey and pale rose colours. Very low NDVI values (for example, 0.1 or less) represent areas of barren rock, sand, or asphalt. Moderate NDVI values (approximately 0.2 to 0.5) represent sparse vegetation. Dense vegetation or crops at their peak growth stage are represented by High NDVI values (approximately 0.6 to 0.9).
This parameter is associated with the presence and healthiness of a plant. In this case, the bright green and yellow colours correspond to the algal bloom probably caused by the discharge of chemicals in the lake, which cause the overproduction of algae triggering a process called eutrophication.
Fig. 3 Cloud-based Change detection imagery service calculating NDVI index on-the-fly show the presence of vegetation, in Inner Murchison Bay, Lake Victoria between 2015 (left) and 2018 (right). The green and yellow colours, representing high NDVI values, in the right imagery show the presence of high concentration of vegetation into the water.
The benefits of analytics-ready imagery services on the cloud
As showed in the previous section, cloud-based imagery services are crucial to fulfil the information needs to boost sustainable development and planning, providing up-to-date and sub-metric information data that can be used for the following purposes:
- As a base-map layer;
- To identify land that is suitable for development;
- To map and create digital models of features such as buildings, river streams, landmarks;
- To monitor the progress of projects;
- In combination with business intelligence software to compare project delivery figures against project areas;
- To identify and map informal settlements and visual counts of informal structures.
Very often, the images that governments and private companies have access to are outdated by two, three, or even more years. Thus, it is of utmost importance to provide them with timely updated imagery.
Additionally, some entities may rely on free sources of imagery that could be used for base-mapping, but the resolution of this data generally does not meet the parameter of sub-metric resolution that is needed for a thorough analysis and identification of independent structures and buildings. Another challenge when monitoring the progress of a project over a period of time is the amount of data and the large storage needed to store the imagery.
Delivering the data through a friendly-user imagery service provides a solution to all these challenges. In order to trigger the imagery service, users just need to define their area of interest, the frequency with which they need the data and their application or resolution needs. This enables users to easily access fresh, reliable and quality-assured imagery, directly onto their apps and desktops.
Hosting the data in Amazon Web Services using Esri ArcGIS technology, allows the user to have access from various devices and locations. The data doesn’t need to be downloaded nor stored. All the imagery can be accessed on the cloud and users can utilise the multi-temporal imagery service to start building valuable applications for monitoring, change detection and precision insights on the fly. In addition, the imagery service can be easily integrated through plugins in the users preferred GIS software packages.
Whether users are future-focused or exploring the past, they can get constant and reliable access to seamless data on the cloud and get any area of interest, every day, directly into their applications and desktops.
All picture Credits: Deimos Imaging, an UrtheCast Company
