The BirdLife South Africa Community Bird Guides are well regarded and respected members of the South African birding community.
BirdLife South Africa has an extensive network of members, supporters, and birders locally and abroad.
AI-based crack gauge for rockfall
AI-based crack guage
KNPS
AI-based crack gauge
TV chosun
AI-based crack gauge for rockfall is a device that monitors the occurrence of rockfall and the crack displacements in real-time by installing an observation sensor in a rockfall risky area located along the trail. Since 2013, automatic and manual crack gauges have been installed on steep slopes with a high risk of collapse, and 525 units are currently in operation at 174 locations. The rockfall measuring device is divided into risk levels of 'interest, caution, alert, and serious'. In the interest stage, regular and frequent inspections are carried out. In the caution stage where cracks are less than 5 mm and less than 2°, monitoring is strengthened. In the alert stages, precise investigation and action plans for the disaster are prepared. In the serious stage, the adjacent trails are controlled and emergency measures such as rockfall removal are implemented.
Prior to the installation of the AI-based crack gauge, a dedicated investigation team composed of geologists and disaster prevention experts was established in advance to systematically manage rockfalls and steep slopes to investigate areas with risk of rockfall accidents along the trails of national parks. In addition, the safety hazardous areas were graded from A to E according to the degree of risk, steepness, and other geologic characteristics and converted into databases.
81 rockfall events have occurred in the national park during the last 10 years, resulting in 3 deaths and 6 injuries, damaging properties of about KRW 2.1 billion. However, since 2018, when the AI-based crack gauge was used, there has been no fatality or injury to visitors due to rockfalls. In addition, it took a lot of time and labor to inspect all the crack gauges installed throughout the national park one by one. With the saved time park rangers can concentrate more on park other management activities, which greatly improved the internal satisfaction.
AI-based Intelligent CCTV is a scientific safety management system that uses deep learning technology to control emergencies in real-time image analysis. By recognizing and analyzing abnormal behavior patterns, such as intrusion, screaming, wandering, etc., a warning broadcast is immediately sent to the site and delivered to the control system, following the emergency responses.
In addition, in the case of marine/coastal national parks with a high risk of safety accidents due to tides and tides, the broadcast of tide times is automatically issued to the site. Intelligent CCTV was installed in 2020 and is currently being operated in 89 places in 15 national parks.
The most important enabling factor is to select the optimal location where the equipment can be operated effectively. Intelligent CCTV was installed by selecting areas where drowning accidents occurred frequently in the past. Another success factor is having a set of systems to deal with emergencies. When the AI alarm system is activated, the general control center in KNPS HQ checks real-time streaming to quickly grasp the situation and then rescue teams in national parks on the spot to start rescue operations.
AI-based intelligent CCTV is a scientific safety management system using deep learning technology. In order to continuously improve the accuracy of deep learning, experts continue to maintain the software and provide technical support in the field so that it can be managed stably. As data for deep learning is accumulating, it is expected that the operating level of the system will be increased. Based on these achievements and limitations, it is necessary to improve the numerous CCTVs that have been monitored by manpower using this innovative technology gradually in connection with the KNPS safety management system.
Workflow analysis, Partnership building, and Overall planning
Years of research and conservation practices have not only stressed the importance of biodiversity data but also revealed the flaws of current workflow, ranging from inefficient data management, lack of data integration, to limited public-accessible data applications. Moreover, such workflow is mainly man-powered and often involves a lot of repetitive work, taking up huge amount of conservationists’ time.
Following the rapid development of technology, we have gradually realized the potential of technology to bring solutions to our “pain points” for long. In order to utilize technology tools in places in most needs, a systematic review and analysis of the current workflow was conducted to identify bottlenecks with high priorities and the possible solutions. The contemplation began in May 2018 and was materialized starting from Jun 2019 after potential technical partners emerged. Based on the systematic workflow analysis and close partnership, we made a step-by-step plan, aiming at developing modules one by one, considering our limited resource and manpower (e.g., from community-based camera trap monitoring assistant app, to BiA tool, to citizen science data visualization platform, to camera trap data management system).
A systematic review of current workflow and gap analysis that indicates where technology tools can help
Reliable and supportive technical partners (through trial and error)
An ambitious yet practical plan
Engaging various colleagues in the discussion of workflow and technical solutions is helpful to collect more valuable ideas.
Different technical companies have different work styles. Choose the ones that suit your work style and values.
To enable automatic and instant biodiversity impact assessment enquiry, the BiA tool has been developed to facilitate enquiry services for land planners and other interested parties via Azure platform. The BiA tool works by overlaying the enquiry site or region (or existing construction projects) with multiple geographic layers including species distribution and protected area range to investigate if the site or region is within certain distance (e.g., 3 km, 5 km) from and may cause impact on endangered species habitat and/or protected areas. The assessment reports illustrate ecological and environmental risks of construction projects for decision-makers and could hopefully promotes them to take biodiversity into consideration.
A brief timeline of the BiA tool:
Apr-Jun 2020: team formation, requirement communication, system development plan
Jul-Sept 2020: tool development
Oct 2020: trial test, application and dissemination
(in preparation) Apr-Sept 2022: system upgrade
Years of data collection accumulation and constant thinking of data application approaches.
Theoretical & technical basis accumulated from long-term research and conservation practice.
Promotion of the BiA tool to its potential users, like governments, investors, and enterprise.
Keeping track of tool operation and user feedback to devise further upgrade of the tool.
Data application is the foremost step in the whole data workflow, where the data turns into valuable information for stakeholders. Effective data application reports should bear the audience in mind (e.g., being concise and focused).
The complete of development and releasing is not the last step for a tool. Finding potential users and persuading them to use the tool is also very important. A tool has to be used to provide the most value.
Coordination Platform for Sustainable Pasture Management
A Pasture Coordination Platform was organized in Armenia as a horizontal management network among relevant stakeholders on national and sub-national level. Each party is represented by a spokesperson, who coordinates the functions of the party within the Platform and ensures information flow. A secretariat ensures the operation of the Platform. The rationale for creation of the Platform was the need to promote effective cooperation, exchange of information, as well as coordination of activities among the projects implemented in Armenia, focusing on sustainable management of natural fodder areas.
Since 2018 the Platform has evolved and now more than 10 organizations, institutions, projects and public administration bodies are involved in the Platform’s activities, aiming to ensure viability of programs and investments in the area of animal farming, increase economic opportunities of communities and support income growth of rural residents in Armenia. Key objectives of the Coordination Platform are:
Coordination, exchange of information exchange and experience, identification of potential cooperation areas
Implementation of joint projects, activities
Advocating and supporting development of relevant state policy and legislation promoting sustainable use and management of natural fodder areas
The platform has a clear aim: "to improve the situation/ livelihood of the rural population which depends on natural fodder areas while sustainably using and conserving these natural ecosystems”.
The need for coordination, cooperation and exchange was felt by parties both from government as well as non-government organizations.
A memorandum was officially signed to establish the platform.
All members have clearly distinguished functions.
Active participation of the community stakeholders in decision making and coordination of the local projects was crucial. Placing the local working groups in charge of the local implementation not only generated a high level of ownership of the project and ensured the engagement of the community.
The coordination with other development organizations on the local scale was a key factor. The harmonization of these different local interventions resulted in a comprehensive, positive change for the communities. Each intervention was complimented by the others and would not have achieved the same results as an isolated activity.
Based on the memorandum of understanding, the common interest and need of all stakeholders in the platform to cooperate increased their commitment and ensured the continuity of the process.
Multi stakeholder advisory bodies face high risks from unforeseen changes in governmental institutions or even within their own parties. The meticulous documentation of agreements and activities has proven to be an important measure for dealing with this risk.
Maintaining pastures as a natural resource is easily to been done by the application of GIS and remote sensing tools to develop accurate classification maps, e.g. pastures, hay meadows, grassland. The combination of digital data and spatial technology enables detailed and useful monitoring of aboveground green vegetation biomass and grassland composition. Besides, resources and attributes can be monitored for knowledge management and long-term decision planning.
Mapping of pasture/ grassland ecosystem services and understanding of its contribution to human well-being
Facilitate regular monitoring at the management level
Short-term study of the positive and negative effects on pasture or grassland areas
Existence of relevant legal bases and close involvement of relevant bodies in the planning process
All factors that may affect pastures should be identified as spatial data
Mapping and monitoring changes in grassland vegetation cover is essential to understand grasslands dynamics
Reliable monitoring of changes in vegetation cover in grasslands is crucial for accurate and sustainable land management
Gathering more field/ ground truthing data was one of the important notes
It is vital to test and demonstrate different geospatial analyses to showcase what measures have the most impact on which erosion/degredadion situations and foster understanding for the solutions.
