Tree Biomass Estimation in Agroforestry for Carbon Farming: A Comparative Analysis of Timing, Costs, and Methods
Abstract
1. Introduction
2. Traditional and Innovative Methods for Estimating AGB in AFSs
2.1. Traditional Field-Destructive AGB Measurements
2.1.1. Field Activities
2.1.2. Data Analysis for Allometric Equation Development
2.1.3. Advantages and Limitations of Destructive AGB Measurements
2.2. Innovative Methods: Remote Sensing-Based AGB Estimations
2.2.1. Remote Sensing and Machine Learning
2.2.2. Satellite-Based AGB Estimation
2.2.3. UAV-Based AGB Estimations
2.2.4. Root Biomass Quantification Through Ground Penetrating Radar (GPR)
2.3. A Case Study in Follonica (Tuscany, Italy)
2.3.1. Field-Destructive AGB Measurements
2.3.2. Satellite-Based AGB Estimations
2.3.3. UAV-Based AGB Estimations
2.3.4. Comparison of Timing and Costs from the Activities in Follonica
3. Discussion and Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
AFS | Agroforestry Systems |
AGB | Above Ground Biomass |
BGB | Below Ground Biomass |
CRCF | Carbon Removals and Carbon Farming Certification |
DBH | Diameter at Breast Height |
GCP | Ground Control Point |
GNSS | Global Navigation Satellite System |
GPR | Ground Penetrating Radar |
GSD | Ground Sampling Distance |
H | Tree Height |
RMSE | Root Mean Square Error |
RTK | Real Time Kinematic |
UAS | Unmanned Aerial System |
UAV | Unmanned Aerial Vehicle |
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Type | Equation | n | R2 | RMSE | Reference |
---|---|---|---|---|---|
Linear simultaneous AFSs (Uganda)—Various species | 12–16 | 0.30 | 0.761 | [60] | |
0.739 | 0.208 | ||||
0.759 | 0.189 | ||||
Teobroma cacao in AFSs (Cameroon) | 35 | 0.942 | 0.198 | [42] | |
0.945 | 0.190 | ||||
Wild cherry trees (Prunus avium L.)—AFSs (Germany) | 70 | 0.982 | - | [61] | |
0.782 | - | ||||
Quercus rubra (Canada) | 12 | 0.984 | 30.3 | [21] | |
Juglans nigra (Canada) | 16 | 0.982 | 18.2 | ||
Picea abies (Canada) | 13 | 0.988 | 23.15 | ||
Robinia pseudoacacia (Canada) | 10 | 0.967 | 19.09 |
Country | Cost per Tree (€/Tree−1) | Source |
---|---|---|
Italy | 37.09 | Local public prices (Tuscany region) |
Spain | 79.26 | Local public prices (Zamora Province) |
Belgium | 300–500 | Local private prices (Hainaut Province) |
Satellite | Data Source | Access Link | Type |
---|---|---|---|
Sentinel-2 | Copernicus Open Access Hub | Sentinel Hub | Free |
Airbus Pleiades | Airbus | Airbus Portal | Commercial (from 17 to 50 EUR/sq KM) |
Landsat-8/9 | USGS Earth Explorer | Earth Explorer | Free |
Sentinel-1 (SAR) | Copernicus Open Access Hub | Sentinel Hub | Free |
ALOS-2 PALSAR | JAXA | JAXA Data Portal | Commercial |
GEDI (LiDAR) | NASA Earthdata | NASA Earthdata | Free |
ICESat-2 | NSIDC | NSIDC | Free |
Element | Brief Description | Price Range (€) |
---|---|---|
Satellite-based script development | Python-based (software version 3.10) script for pre- and post-processing satellite imagery, as well as for developing, testing, and deploying the ML-based model to extrapolate AGB layers and related information. | 15,000–20,000 |
Biomass model run (per execution) | - | 500–1000 |
Commercial satellite data | Time to be considered for new satellite imagery tasking: 1 to 2 weeks (depending on tasking requirements and cloud presence). | 750–1500 |
Open-source satellite data | - | Free |
Parameter | Unit | Quantitative Value | Qualitative Value |
---|---|---|---|
pH | - | 6.56 | moderate acidity |
EC | mS/cm−1 at 25 °C | 0.109 | low |
TN | N g/kg−1 | 0.67 | low |
P | P2O5 mg/kg−1 | 8.66 | low |
K | K2O mg/kg−1 | 230 | high |
Ca | Ca mg/kg−1 | 1197 | high |
Mg | Mg mg/kg−1 | 153 | high |
Mg/K | ratio | 0.67 | low |
SO | % | 1.3 | low |
C/N | ratio | 11 | medium-low |
CEC | meq/100 g−1 | 11.23 | low |
texture | - | sandy clay loam |
Acquisition Number | Acquisition Date Range |
---|---|
1 | 1 April–10 May 2024 |
2 | 1 July–10 August 2024 |
3 | 1 October–15 October 2024 |
4 | 1 January–10 February 2025 |
5 | 1 March–9 April 2025 |
Element | Brief Description | Price Range (€) |
---|---|---|
Drone and accessories | DJI Mavic 3 Multispectral with RTK module, extra batteries, landing pad | 5000–5500 |
GNSS and surveying | Emlid Reach RS2+, tripod, survey pole, levelling base | 2300–2800 |
GCPs | Custom methacrylate plates | 40–170 |
Communications system | SIM cards for device connectivity | 30–60 (per unit/year) |
Analysis and modelling software | Pix4Dmapper, Pix4Dmatic, Pix4Dsurvey (licences) | 8500–10,000 |
GIS and geospatial analysis | QGIS (free and open-source software version 3.40.9) | Free |
AGB Estimation Method (€ ha−1) | Analytical Estimate (€ ha−1) | Synthetic Estimate (€ ha−1) | Off-Farm Procurement (€ ha−1) |
---|---|---|---|
destructive sampling | 965.19 * | 929.89 | 1157.14 |
non-destructive sampling (allometric equations) | 266.44 * | - | - |
UAV-based measurement | 400–670 | 430.00 | 650.67 |
Satellites-based (optical, LiDAR and SAR) measurements | 1250–2500 | - | - |
Destructive Sampling | Analytical Estimate (INNO4CFIs Real Costs) | Synthetic Estimate (Regional Price List) | Off-Farm Procurement (Private Market) |
---|---|---|---|
cost per tree (€) | 30.03 | 28.93 | 36.00 |
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Conti, N.; Della Rocca, G.; Franciamore, F.; Marra, E.; Nigro, F.; Nigrone, E.; Ramadhan, R.; Paris, P.; Tárraga-Martínez, G.; Belenguer-Ballester, J.; et al. Tree Biomass Estimation in Agroforestry for Carbon Farming: A Comparative Analysis of Timing, Costs, and Methods. Forests 2025, 16, 1287. https://doi.org/10.3390/f16081287
Conti N, Della Rocca G, Franciamore F, Marra E, Nigro F, Nigrone E, Ramadhan R, Paris P, Tárraga-Martínez G, Belenguer-Ballester J, et al. Tree Biomass Estimation in Agroforestry for Carbon Farming: A Comparative Analysis of Timing, Costs, and Methods. Forests. 2025; 16(8):1287. https://doi.org/10.3390/f16081287
Chicago/Turabian StyleConti, Niccolò, Gianni Della Rocca, Federico Franciamore, Elena Marra, Francesco Nigro, Emanuele Nigrone, Ramadhan Ramadhan, Pierluigi Paris, Gema Tárraga-Martínez, José Belenguer-Ballester, and et al. 2025. "Tree Biomass Estimation in Agroforestry for Carbon Farming: A Comparative Analysis of Timing, Costs, and Methods" Forests 16, no. 8: 1287. https://doi.org/10.3390/f16081287
APA StyleConti, N., Della Rocca, G., Franciamore, F., Marra, E., Nigro, F., Nigrone, E., Ramadhan, R., Paris, P., Tárraga-Martínez, G., Belenguer-Ballester, J., Scatena, L., Lombardi, E., & Garosi, C. (2025). Tree Biomass Estimation in Agroforestry for Carbon Farming: A Comparative Analysis of Timing, Costs, and Methods. Forests, 16(8), 1287. https://doi.org/10.3390/f16081287