GHG mitigation requires measurable, accurate, and well-targeted climate action. A Greenhouse Gas Inventory, or GHG Inventory, provides an important foundation for identifying emission sources and developing effective emission reduction strategies.
The AFOLU sector, which stands for Agriculture, Forestry and Other Land Use, plays a crucial role in the carbon cycle. This role is also relevant in rapidly changing urban areas, where land fragmentation, settlements, infrastructure development, and limited green spaces create unique challenges for greenhouse gas accounting.
Urban areas therefore require specific approaches when implementing a GHG Inventory. This article examines alternative methods for conducting GHG inventories in urban AFOLU microsectors, with a particular focus on the forestry sector and urban forests in DKI Jakarta as a case study.
Unique Characteristics of Urban Land Cover and GHG Inventory Challenges
Urban ecosystems contain a wide variety of land cover types, ranging from urban forests and residential yards to settlements, agricultural land, parks, and other green open spaces. This diversity reflects the complex interaction between human activities and the natural environment.
Based on the IPCC Guidelines for National Greenhouse Gas Inventories, urban land can be classified into several major land-use categories.
Urban forests, parks with large trees, and other green areas that meet the applicable criteria for forest classification may be categorized as forest land. These criteria can include minimum area, canopy dimensions, and percentage of tree cover.
Land used for agricultural cultivation, plantations, fruit production, or other cropping systems can be categorized as cropland. This may include residential yards planted with vegetables, fruit trees, or other cultivated plants.
Open areas dominated by grasses and shrubs, such as sports fields and urban parks with low vegetation, can be classified as grassland.
Residential and commercial areas dominated by buildings, roads, and infrastructure are generally categorized as settlements.
Wet areas such as lakes, ponds, marshes, and other water-related ecosystems may fall under the wetlands category.
Land that does not fit into the major categories may be classified as other land, depending on the applicable inventory methodology and land-use classification system.
Urban forests, which are often established or managed as man-made forests, may be distributed across small and fragmented polygons with highly variable tree species and vegetation structures.
This condition creates several challenges for urban GHG inventories, including high land-cover variability, small and scattered monitoring areas, rapid land-use change, and limited access to certain locations.
Role of Technology in Urban GHG Inventory
Advances in information technology and remote sensing provide significant opportunities to improve the accuracy and efficiency of urban GHG inventory activities.
High-resolution satellite imagery, including imagery from systems such as WorldView and Pleiades, can support detailed land-cover identification and delineation. In some applications, high-resolution imagery can even help analysts identify individual tree crowns and small vegetation patches.
Drone technology can also support urban GHG monitoring. Drones equipped with RGB cameras, multispectral sensors, or LiDAR can collect detailed information over relatively small areas quickly and efficiently.
These technologies are particularly useful for urban forests because the vegetation is often fragmented and distributed across locations that may be difficult to monitor using conventional field surveys alone.
Using LiDAR for Biomass and Carbon Estimation
LiDAR data can be highly valuable in urban GHG inventory activities because it can provide three-dimensional information about vegetation structure.
LiDAR can be used to estimate tree height, canopy structure, vegetation density, and other parameters that can support biomass calculations.
When combined with appropriate field measurements and allometric equations, LiDAR data can improve estimates of above-ground biomass and carbon stocks within urban forests.
This approach is particularly useful in areas with complex vegetation structures, where traditional two-dimensional mapping may not provide sufficient information about tree height and canopy volume.
GIS for Urban GHG Inventory Management
Geographic Information Systems (GIS) play an important role in managing and analyzing urban GHG inventory data.
GIS can integrate information from satellite imagery, drones, LiDAR, field surveys, government databases, and other sources into a single spatial analysis environment.
This makes it easier to map carbon stocks, monitor land-use changes, identify potential emission sources, and visualize the results of greenhouse gas inventories.
GIS can also support modeling and simulation to estimate future changes in land cover and associated GHG emissions.
For example, spatial models can be used to assess the potential consequences of converting agricultural land or green open spaces into residential and commercial areas.
Online and mobile platforms can also support field-data collection, data validation, and public dissemination of GHG inventory information.
When properly designed, these platforms can encourage public participation through citizen science, where communities contribute observations and environmental data to support monitoring activities.
Adaptive GHG Inventory Methodology for Urban Areas
Implementing a GHG Inventory in urban areas requires an adaptive and innovative methodology that reflects the characteristics of urban landscapes.
Accurate land-cover mapping and monitoring can begin with the use of high-resolution satellite imagery, drones, and LiDAR data. Remote sensing results should then be validated using appropriate field observations.
Land-cover stratification should consider factors that influence carbon dynamics, including vegetation type, vegetation density, stand age, land management, and environmental conditions.
Information from government agencies, including urban parks and forestry offices, spatial planning agencies, and other relevant institutions, can help improve the accuracy of land-cover classification and stratification.
Permanent Sampling Plots for GHG Monitoring
Permanent sampling plots can be established across different land-cover strata to support regular measurements of carbon stocks and relevant emission factors.
Repeated measurements allow researchers and government institutions to monitor changes in vegetation biomass and carbon storage over time.
National standards and technical guidelines can be used as references when determining plot design, sampling intensity, measurement procedures, and acceptable sampling errors.
The use of suitable allometric equations is also important when estimating tree biomass. Equations should be selected based on tree species, forest characteristics, environmental conditions, and available scientific references.
Using inappropriate equations can introduce significant uncertainty into biomass and carbon-stock estimates.
Carbon Pools and Other GHG Sources in Urban AFOLU
A comprehensive urban AFOLU inventory should not focus only on living tree biomass.
Other carbon pools and emission sources may also need to be evaluated, including soil organic carbon, dead organic matter, litter decomposition, and emissions associated with land-use conversion.
In rapidly developing urban areas, changes in land use can become a significant source of emissions.
For example, the conversion of agricultural land, vegetation areas, or other open spaces into residential development may change carbon stocks and affect the overall GHG balance of an area.
Monitoring these changes is therefore important for producing accurate urban greenhouse gas inventories.
Calculating GHG Emissions in the AFOLU Sector
In a simplified approach, GHG emissions can be calculated by multiplying activity data by the relevant emission factor.
GHG Emissions = Activity Data × Emission Factor
For land-use activities, the calculation may be expressed as:
Emissions = Activity Data (ha) × Emission Factor (tCO2e/ha)
Activity data may represent changes in land-cover area, while emission factors describe the amount of greenhouse gas emissions or carbon-stock changes associated with a particular activity or land-use transition.
However, the actual methodology may become more complex depending on the carbon pools, greenhouse gases, land-use categories, time periods, and methodological tiers being applied.
Land-Use Change as a Major Urban GHG Source
In urban AFOLU systems, an important source of greenhouse gas emissions may come from changes in non-forest land use.
The conversion of agricultural land, green open spaces, and vegetated areas into settlements and infrastructure can alter carbon stocks and reduce the ability of urban landscapes to store carbon.
For this reason, monitoring non-forest land-use change should become an important component of urban GHG inventory systems.
Historical satellite imagery can be combined with current spatial data to identify land-use transitions and calculate changes over time.
Regular monitoring can also help governments identify areas experiencing rapid development pressure and evaluate the potential climate implications of future urban expansion.
GHG Inventory Reporting and Quality Control
GHG inventory reporting should follow relevant national regulations, technical standards, and international guidelines such as those developed by the IPCC.
Transparent documentation is particularly important. Inventory reports should clearly explain data sources, methodologies, assumptions, emission factors, spatial boundaries, calculation periods, and uncertainties.
Quality assurance and quality control procedures should also be implemented to identify inconsistencies, calculation errors, missing data, and other potential problems.
A well-documented methodology makes it easier to reproduce calculations, compare inventory results between years, and improve the quality of future assessments.
Optimizing Urban GHG Inventory Systems
Several strategic actions can strengthen the implementation of GHG inventories for the urban AFOLU sector.
Human resource capacity needs to be improved through technical training, professional development, and certification. Personnel involved in GHG inventories should understand remote sensing, field measurements, carbon accounting, data management, and relevant reporting standards.
An integrated GHG database is also important. Data from different government agencies, research institutions, universities, and field surveys should be managed within a consistent information system.
Cooperation between stakeholders can help reduce data duplication and improve the availability of information needed for inventory calculations.
Information technology should also be used to automate data processing, monitoring, reporting, and visualization wherever possible.
Public Participation in Urban GHG Monitoring
Public awareness and participation can strengthen urban environmental monitoring programs.
Local communities can contribute information related to tree planting, changes in green spaces, vegetation conditions, and other environmental observations.
Citizen science platforms can help connect community observations with official monitoring systems, although appropriate validation procedures are still needed to ensure data quality.
Public education about GHG emissions and urban carbon stocks can also help communities understand the importance of protecting urban forests and green open spaces.
Urban Forests in DKI Jakarta as a GHG Inventory Case Study
Urban forests in DKI Jakarta illustrate how complex urban landscapes can require a combination of remote sensing, spatial analysis, field measurements, and institutional collaboration.
Urban vegetation is often fragmented among parks, roadside areas, urban forests, residential areas, institutional land, and other green spaces.
Because these areas differ in vegetation structure and management, a single generalized emission factor may not always adequately represent all urban vegetation.
Stratification and representative sampling can therefore help improve estimates of biomass and carbon stocks.
Combining satellite imagery, drones, LiDAR, GIS, field measurements, and administrative data can create a more comprehensive understanding of urban carbon dynamics.
The Future of GHG Inventory for Urban AFOLU
An adaptive and innovative approach is essential for producing reliable GHG emission estimates in rapidly changing urban environments.
The use of remote sensing technology, representative land-cover stratification, permanent sampling plots, appropriate allometric equations, and accurate emission factors can significantly strengthen urban GHG inventory systems.
At the same time, collaboration among local governments, researchers, universities, communities, and other stakeholders is essential for maintaining consistent and reliable data.
The urban forest case study in DKI Jakarta demonstrates the potential for combining technology and institutional cooperation in greenhouse gas monitoring.
By continuously improving data quality, monitoring systems, technical capacity, and methodological approaches, urban AFOLU GHG inventories can provide stronger support for climate change mitigation policies.
Ultimately, a reliable GHG inventory can help cities identify major emission sources, monitor carbon stocks, evaluate land-use changes, and develop more effective strategies for sustainable and climate-resilient urban development.