Semantic Conceptual Framework for Environmental Monitoring and Surveillance—A Case Study on Forest Fire Video Monitoring and Surveillance

This paper presents a semantic conceptual framework and definition of environmental monitoring and surveillance and demonstrates an ontology implementation of the framework. This framework is defined in a mathematical formulation and is built upon and focused on the notation of observation systems. This formulation is utilized in the analysis of the observation system. Three taxonomies are presented, namely, the taxonomy of (1) the sampling method, (2) the value format and (3) the functionality. The definition of concepts and their relationships in the conceptual framework clarifies the task of querying for information related to the state of the environment or conditions related to specific events. This framework aims to make the observation system more queryable and therefore more interactive for users or other systems. Using the proposed semantic conceptual framework, we derive definitions of the distinguished tasks of monitoring and surveillance. Monitoring is focused on the continuous assessment of an environment state and surveillance is focused on the collection of all data relevant for specific events. The proposed mathematical formulation is implemented in the format of the computer readable ontology. The presented ontology provides a general framework for the semantic retrieval of relevant environmental information. For the implementation of the proposed framework, we present a description of the Intelligent Forest Fire Video Monitoring and Surveillance system in Croatia. We present the implementation of the tasks of monitoring and surveillance in the application domain of forest fire management.

The Impact on Ecosystem Services and the Satisfaction Therewith of Community Forest Management in Northern Thailand

Forest ecosystems provide myriad services that are beneficial to local livelihoods. Successful community forest management (CFM) enhances the provision, overall benefit, and effectiveness of the regulation of ecosystem services and contributes to forest conservation efforts. The study area was a deciduous forest in the Ban Mae Chiang Rai Lum Community Forest, which is located in Pa Mae Phrik National Forest Reserve in Thailand’s northern province of Lampang. A systematic sampling of the forest area was conducted, and survey plots were established. A field survey documented 197 plant species from 62 families. A questionnaire that focused on CFM engagement behavior and ecosystem service satisfaction levels was used to interview household representatives. The study found that levels of engagement and the effectiveness of forest management were directly related; increased CFM effectiveness leads to improved ecosystem services. Participation in CFM can improve ecosystem services and enhance livelihoods. Specifically, participation in decision making, forest fire management, check dam construction, benefit sharing, and in forming effective forest regulations positively impacted ecosystem services. In contrast, employing forest patrols adversely affected those services. This knowledge is useful for identifying policies and practices that can maximize ecosystem services to enhance livelihoods and safeguard the forest’s vitality.

Fire Drivers Affecting Forest Fire Occurrences in the Tropical Mixed Broad-leaved Forests of Nepal

Forest fires triggered by various natural and anthropogenic drivers are increasing and threatening forest ecosystems across the globe. In Nepal, the high value Tropical Mixed Broad-leaved Forests are prone to fire caused by both natural and anthropogenic drivers. Thus, understanding fire drivers and their effect is important for the sustainable forest fire management. However, the preceding studies on forest specific fire drivers and their effect are limited. This research has identified the fire drivers and assessed their effect to fire occurrences in the Tropical Mixed Broad-leaved Forests of Nawalparasi District, Nepal. Fire drivers were identified and prioritized by participatory approaches. The fire incidences and burnt areas were obtained from the MODIS fire data (2001–2017). The results revealed altogether 20 drivers including eight natural and 12 anthropogenic. Based on the public perception and magnitude of forest fire, among the natural drivers, temperature, precipitation, forest fuel, aspect, elevation and slope were the major drivers. Likewise, among the anthropogenic drivers, forest distance from roads and settlements showed significant effect. The natural drivers, ambient temperature >30ºC and annual precipitation <2400 mm, revealed signi-ficant impacts on forest fire. Likewise, forests situated at lower elevation (<500 m), and southern and eastern aspects were highly vulnerable to fire. Considering anthropogenic drivers, forest lying within 500 m from the roads and settlements were highly vulnerable to fire. Among the forest types, the Hill Sal Forest was more affected. Future strategies should address the major fire drivers, construction of adequate fire lines and conservation ponds for the sustainable forest management.

Developing models to establish seasonal forest fire early warning system

During a typically dry season in Sumatra or Kalimantan, the forest fire starts. In 2015, an El Nino year, forest fires in Sumatra and Kalimantan ranked among the worst episodes on record. Understanding the connection between accumulated monthly rainfall and the risk of hotspot occurrence is key to improving forest fire management decision-making. This study addresses model development to predict the number of 6-month fire hotspots, by combining the prediction of rainfall with hotspot patterns. Hotspot data were obtained from the Fire Information for Resources Management System (FIRMS) for the period of 2001–2018. For rainfall prediction, we used the output model of the European Centre for Medium-Range Weather Forecasts (ECMWF). The threshold of more than 10 hotspot events has been used to establish hotspot climatology. To get a threshold for rainfall that can cause forest fires, we used the Pulang Pisau rain station. We applied two rainfall thresholds to determine three categorical forecasts (low, moderate, high) as environment quality indicator. The two thresholds are 100 mm/month for the lower threshold and 130 mm/month for the upper threshold. The verification of the observational data showed an accuracy of > 0.83, which is relatively consistent and persistent with forest fire events. The weakness of this system is that it cannot determine the exact location of the forest fire because the spatial resolution used is 0.25 degrees. The predictions of the monthly climate index values were reasonably good suggesting the potential to be used as an operational tool to predict the number of fire hotspots expected. The seasonal forest fire early warning system is expected to be an effort to anticipate forest fires for the next six months. The modeling strategy presented in this study could be replicated for any fire index in any region, based on predictive rainfall information and patterns of the hotspot.

Institutional fragmentation of peat fire management in Indonesia: a knowledge management perspective

The importance of intersectoral collaboration in policy implementation has been widely accepted. Concepts of intersectoral collaboration and policy coordination are theoretically appealing; however, it is challenging to implement in practice, including in forest fire management. This paper aims to map the institutions on forest fire management and analyze the rationality in using knowledge in their duties and authorities. Using stakeholder mapping combined with the Concern-Knowledge-Action approach, this study is conducted at the national level in Indonesia, and takes two sub-national levels, South Sumatera and Central Kalimantan, as the case study. There are many institutions involved in fire management in all governance levels, including at the provincial-district level, as well as at the sub-district-village level, but the institutional fragmentation in peat fire management is still found. In managing fire in South Sumatera and Central Kalimantan, it is not handled by a specific institution having the most influential and important positions. They have different authorities but the same potential power to prevent and combat fire. A complex interconnection among them indicates the need for effective institution integration. Less connectivity among the knowledge pool is also found, especially between private – community, NGO – academia, and government – community. Finally, knowledge improvement on fire prevention method especially in defining a community livelihood offset, as well as the ex-post fire management (measuring the level of fire impact and its recovery methods) is needed to fill the gap of knowledge. A stakeholder Forum is one of the options to improve intersectoral coordination in managing forest fire in peatland and enhance the effectiveness of knowledge sharing. At community level, conducting informal discussion and capacity-building programs would be feasible options for better coordination and improving knowledge.

REVIEW OF OPEN SOURCE QGIS FORESTRY PLUGINS

Forest industry today has some experience of using Open Source-programs. The article describes the Open Source QGIS plugins to solve the forestry challenges for the forest fire management and forest resources in scientific and applied research. Undertaken analysis will simplify selection of tools for a forest geoinformation project in Desktop and Web versions. A general brief description of modern plugins in QGIS (version 3.18.1) is given, and forestry plugins are characterized. An analysis of external QGIS plugins for working with forest resources and forest fires showed the heterogeneity of research, which has not identified any trends yet. Development of plugins with available data as map services for territories of different spatial coverage may be an option for the future research, while the ability to access archived data is important for the forest industry. The niche of thematic forest tasks in the modern QGIS plugin repository continues to be quite narrow. Transport and environmental applications implemented in GIS tools are more numerous and can solve some tasks of a forest project. Such review of plugins’ functionality should be done on a regular basis, following new developments and new versions of QGIS software.

Application of Multi-Criteria Decision Making Models in Forest Fire Management

The study on effective factors of forest fire prevention policy is helpful to reduce forest fire impacts on extensive environmental damage in the long-term period. In other words, forest fire management is the result of a complex interaction among criteria. The present study aims to create a scientific analysis of the most effective criteria based on TOPSIS and SAW methods in the Arasbaran forest. The five top optimal criteria selection by TOPSIS method introduced that “association and cooperation between the executive and responsible institutions” have the first rank (CCi+=0.85), “Lack of deterrence law in dealing with forest fire offenders in human–caused forest fires” has the second rank (CCi+= 0.84) and followed by “Lack of up-to-date scientific information on susceptible areas in the region”, “Increasing the cooperation of NGOs and increase public trust”; and “Lack of forest road network access to ignite regions” (CCi+= 0.789; 0.787; 0.77, respectively). The five top optimal criteria resulting from the SAW method showed that “Local people participations” provide the highest score (FS=0.39) and followed by “association and cooperation between the executive and responsible institutions (FS=0.39), “Increasing the cooperation of non-governmental organizations (NGOs) and increase public trust” (FS=0.36), “Raising awareness of the position of natural resources among local peoples and attracting their cooperation” (FS=0.35) and “Optimal Use past experiences” (FS=0.34). It is suggested that evaluating the ecological and environmental factors affecting the forest fire occurrence and extension could become a set of complement factors to setting management criteria for demonstrating the best management strategies.