Prospects of Geographic Information System and Multi-Source Data Integration in Enhancing the Accuracy of Above-Ground Biomass and Carbon Stocks Estimation

Citation

Omali, T. U., Akpata, S. B. M., & Onyevu, R. O. (2026). Prospects of Geographic Information System and Multi-Source Data Integration in Enhancing the Accuracy of Above-Ground Biomass and Carbon Stocks Estimation. International Journal of Research, 13(1), 484–492. https://doi.org/10.26643/ijr/2026/23

Omali, Thomas Ugbedeojo (PhD)^1*; Akpata, Sylvester Balm Mifue² (PhD);

Onyevu, Rosemary Onyinye (MSc.)³

¹National Biotechnology Development Agency (NABDA), Abuja, Nigeria.

²Department of Geoinformatics and Surveying, University of Abuja, Nigeria

³Department of Geoinformatics and Surveying, University of Nigeria, Nsukka, Nigeria.

Corresponding Author’s Email Id: t.omali@yahoo.com

Abstract

Evaluating Above-Ground Biomass (AGB) accurately and the successive calculation of carbon stocks are fundamental process for understanding the global carbon cycle, climate change mitigation and sustainable forest management. The traditional field-based methods for AGB and carbon stocks assessment is effective; but then, they involve more cost, time, and they are not scalable to a large area. Thus, the utilization of cutting-edge technology to support the conventional approach is expedient. This study is a mini review that discuss the prospects of Geographic Information System (GIS) and the need to integrate various data in evaluating AGB and carbon stocks. First, literature search was conducted based on which relevant and quality published articles were selected and used to discuss the topic. The result signifies that the spatially explicit GIS-based techniques can be used to create georeferenced estimates of AGB, and carbon sink/stock potential. Also, data from different sources has their unique advantages and drawbacks, which can affect the accuracy of AGB and carbon stocks assessment. However, integrating these data has proven to be highly efficient. Summarily, GIS provides the essential platform for acquiring, integrating, analyzing, and visualizing diverse data sources. This enables the creation of spatially continuous and accurate map of AGB and carbon stocks across landscapes, regions and continents.

Keywords: Above-Ground Biomass, Activity Data, Carbon Sequestration, forests, GIS, REDD+

1. Introduction

The tropical forests are generally characterized by high biomass and carbon content, which makes them to have huge influence on the global carbon cycle. They have unlimited potential for mitigating carbon dioxide (CO₂) emission through suitable conservation and management. On the other hand, deforestation alone is responsible for approximately 12% of the global human-induced emissions of greenhouse gas (GHG) and peat oxidation while fires on degraded peat lands causes another 6% [1]. Also, 10–25% of global emissions resulting from anthropological activities are linked to combined impact of logging and forest re-growth on abandoned land [2,3]. The significance of deforestation in global carbon cycle is apparent. This gave rise to the Bali Action Plan agreed on enhancement of national/international action on climate change mitigation. This includes inter alia, consideration of policy approaches and payment with regards to reducing forest-related emissions in developing nations [4].

The forest biome is a massive carbon pool that can diminish emissions of net GHG through reduction of sources that enhance sinks of CO₂ [5, 6]. Precise spatial and temporal evidence of the existing condition of carbon sources and sinks is required for policy formulation to mitigate greenhouse effects [7]. Monitoring biomass and carbon stocks accurately can now be achieved, thanks to increasingly available of fine resolution and large spatial geographically referenced data. Also, the data can be used to make models that establish the relationship between biomass and their drivers can be used to estimate biomass and carbon at global level. So far, there are many GIS-based spatially explicit approaches for spatiotemporal estimation of carbon sink and stock [8,9]. GIS is a typical processing and visualization tool [9,10]. Nevertheless, much of the existing studies on estimation of terrestrial carbon sequestration and land-use spatial planning have not integrate process-based models with GIS [11].

Mapping and quantifying the tropical AGB is essential in the estimation of carbon dynamics resulting from the modification in LCLU [12]. Though site-specific estimates of AGB based on various modelling is common practice, pan-tropical or global estimates are developed through the combination of ground inventories and remotely sensed forest data. For instance, Saatchi et al. [13] mapped the pan-tropical live biomass at 1-km spatial resolution in 2011. They used a wide-ranging inventory data from 4,079 plots and many remote sensing techniques (optical, microwave and LiDAR sensors). It was revealed that the total of 247 PgC woody biomass was stored in the tropical vegetation. In this, AGB contributed 78% of carbon stocks while 22% of carbon stocks was from below ground biomass. An improved map of the pan-tropical AGB at 500m resolution emerged in 2012 as a result of additional work. The integrated data to create this map were from field inventories, 70 meters resolution LiDAR, and 500 meters resolution MODIS images [12]. Similar to this, Kanja, Zhang, and Atkinson [14] evaluated the capacity to map the AGB of Zambia’s Miombo woodlands using data from Landsat-8 OLI, Sentinel-1A, and extensive national forest inventory.

• Methodology

This review discussed Geographic Information System and multi-source data integration for enhancing the accuracy of above-ground biomass and carbon stocks estimation. Relevant materials used consisted of research articles availed from reputable electronic databases including Web of Science and Scopus. Apart from research articles, grey literatures were equally cited in this paper. The main search for information on the review topic was conducted from September 2025 to November 2025.

• Results and Discussion
  • Role of Geographic Information System for AGB and Carbon Stocks Estimation

A Geographic Information System is a computer-based tool for storing, retrieving, modifying, analysing, and displaying georeferenced data. It is an automated mapping and analysis system, which depends on data that are related to the geographic location of physical entities, and activities. Its intention is to locate and describe places on the Earth’s surface.

GIS data can be used for spatiotemporal monitoring of Land use and Land cover (LULC). LULC and LULC change are used as Activity Data (AD) in carbon stocks assessment. LULC is responsible for approximately 10 percent of global greenhouse gas [15]. According to Yadav [16], the boundaries of LULC classes from satellite-based analysis are typically transferred to a map to create mapping units. These units can then be digitally transformed into a GIS environment to create a vector polygon map. It is noteworthy that GIS is a spatial platform for creating data layers and databases. Apart from accurate and effective management of features [17] such as forests, GIS can be used to easily create spatial models for simulating various situations.

Additionally, georeferenced estimates of carbon sink and stock potential can be produced using spatially explicit GIS-based methods. The GIS is typically used for processing model inputs (e.g., soil texture, land cover) and visualizing the outcomes. For instance, Fatoyinbo and Simard [18] used GIS to combine height data from the Shuttle Radar Topography Mission (SRTM) and spatial coverage of the mangrove generated from Landsat imagery with the intention of computing Africa biomass of mangroves. Furthermore, Malysheva et al. [19] studied the GIS-based assessment of carbon dynamics for Russian forests. In another study, Kehbila et al. [20] carried out a comparative multi-criteria evaluation of Cameroonia’s sustainable development plans and climate policies to create a GIS decision-support tool for the creation of the best possible REDD+ plan.

It is good to note that carbon sequestration provides a major economic value of the ecosystem. Thus, it has become an essential tool for application by United Nations Framework Convention on Climate Change (UNFCCC) in REDD+ programme. Generally, the financial estimation of forest environment services is significant because it assigns an amount on nature. This estimation can correspondingly serve the purpose of guiding climate change policy-makers and decision-makers [21]. The core of REDD+ initiative is the delivery of financial reward to developing nations for keeping carbon stored in their natural forests. The economic worth of carbon sink and stock of forest environment can be mapped and quantified in a GIS environment. In this case, GIS is used for developing database, executing spatial analysis and mapping economic worth. The appraisal process used to determine and monetize the amount of carbon stock and carbon sequestered was measured and validated by Pache et al. [22]. This was accomplished through combination of terrestrial scanning, and monetary valuation to display the sequestered carbon’s spatiotemporal market value

• Data Integration for Estimation of AGB and Carbon Stocks

The ground-based field measurements are the most accurate methods for biomass assessment. It is used to obtain precise data on tree for creating allometric models for computing AGB [23]. But field measurements are possible only on a limited number of points at the sample plot scale. Also, their sampling density are insufficient to afford the requisite spatial variability; and it is usually hard to sample large areas [24]. The ground-based field measurements are also costly, time consuming, and labour intensive [25]. Remote Sensing technology is thus adopted for collecting data or for large-scale mapping and monitoring of various entities such as forest AGB, vegetation structure, vegetation productivity and others [26]. However, remote sensing application has its own associated issues.

By and large, three of the key data sources that are currently being employed for forest AGB mapping and assessment include ground surveys, satellite imagery, and LiDAR. Of course, each data source has its advantages and disadvantages [27]. Thus, the combination many data from various sources can help in analyses of variables that cover a large extent. Integrating multisource data including satellite imagery into a GIS is a potential method for producing spatially-explicit estimates of AGB across a large extent. The majority of current forest estimating research has shown higher accuracy and capacity over a wide area by merging multisource remote sensing data [28]. For example, Forkuor et al. [29] mapped the forest Above-ground biomass by combining Sentinel-1 (S1) and Sentinel-2 (S2) with derivative data. Ma et al. [30] used PALSAR-2 and topographic data to predict AGB in China. Tariq, Shu, Li, et al. [31] effectively analyzed prescribed forest burning and showed Using S1 data.

Many types of satellite data can be used to estimate forest biomass [32] with each type characterized by its advantages and disadvantages. For example, optical sensors were primarily used for forest remote sensing [33]. Although optical data are commonly employed in AGB estimation, their general use is constrained by data saturation issues in places with high vegetation biomass or canopy density, and regular cloud cover. The data from Radar may flow through forest canopies and clouds, unlike passive optical systems [34], however it is impacted by signal saturation [35]. Furthermore, LiDAR data can record a forest’s vertical structure in great detail, hence, it is an excellent substitute for optical and radar data. The 3D data provided by LiDAR is closely linked to forest biomass [36].

• Conclusion and Future Scope

In this paper, we reviewed the application of Geographic Information System, and the significance of data integration in appraising above-ground biomass and carbon stocks. It has been demonstrated in this study that spatially explicit GIS techniques can be used to create georeferenced estimates of AGB, and carbon sink/stock prospects. With GIS, it is easy to process model inputs and also visualize the results. A GIS decision-support tool for creating the best possible REDD+ plan is available through the GIS-based evaluation. Also, many data sources available for mapping and estimation of AGB and carbon stocks has their unique pros and cons. Therefore, integrating them will normally produce highly accurate result.

Finally, there is likelihood that spatially precise outlines of the worth regarding forest carbon sink and stock may soon require at various scales. Thus, be mapped using GIS techniques can be used to map the forest ecosystem and its values. Of course, this will provide managers with a foundation for identifying which areas need additional focus.

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