Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

Cunliffe, Andrew M.; Anderson, Karen; Boschetti, Fabio; Brazier, Richard E.; Graham, Hugh A.; Myers‐Smith, Isla H.; Astor, Thomas; Boer, Matthias M.; Calvo, Leonor; Clark, Patrick E.; Cramer, Michael D.; Encinas-Lara, M.S.; Escarzaga, S. M.; Fernández‐Guisuraga, José Manuel; Fisher, Adrian; Gdulová, Kateřina; Gillespie, Breahna M.; Griebel, Anne; Hanan, Niall P.; Hanggito, Muhammad S.; Haselberger, Stefan; Havrilla, Caroline A.; Heilman, P.; Ji, Wenjie; Karl, Jason W.; Kirchhoff, Mario; Kraushaar, Sabine; Lyons, Mitchell; Marzolff, Irene; Mauritz, Marguerite; McIntire, Cameron D.; Metzen, Daniel; Méndez-Barroso, Luis A.; Power, Simon C.; Prošek, Jiří; Sanz‐Ablanedo, Enoc; Sauer, Katherine J.; Schulze‐Brüninghoff, Damian; Šímová, Petra; Sitch, Stephen; Smit, Julian; Steele, C. M.; Suárez‐Seoane, Susana; Vargas, S. A.; Villarreal, Miguel L.; Visser, Fleur; Wachendorf, M.; Wirnsberger, Hannes; Wojcikiewicz, Robert

doi:10.1002/rse2.228

Cited by 17 publications

(27 citation statements)

References 74 publications

(223 reference statements)

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“…A standard Structure-from-Motion (SfM)-photogrammetric processing workflow with Agisoft Metashape 1.6 (Agisoft LLC, St. Petersburg, Russia) was then employed for extracting dense RGB-coloured 3D point clouds (cf. Cunliffe et al, 2021). We classified the 3D point clouds into vegetation points and ground points (with subclasses tree shadow/no tree shadow) and subsequently computed 3 cm-resolution digital surface models (DSMs) and digital terrain models (DTMs) as well as 1.5 cm-resolution orthophoto mosaics.…”

Section: Small-format Aerial Photography (Sfap) Taken With An Unmanne...mentioning

confidence: 99%

Monitoring Dryland Trees With Remote Sensing. Part A: Beyond CORONA—Historical HEXAGON Satellite Imagery as a New Data Source for Mapping Open-Canopy Woodlands on the Tree Level

Marzolff

Kirchhoff

Stephan

et al. 2022

Front. Environ. Sci.

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Monitoring woody cover by remote sensing is considered a key methodology towards sustainable management of trees in dryland forests. However, while modern very high resolution satellite (VHRS) sensors allow woodland mapping at the individual tree level, the historical perspective is often hindered by lack of appropriate image data. In this first study employing the newly accessible historical HEXAGON KH-9 stereo-panoramic camera images for environmental research, we propose their use for mapping trees in open-canopy conditions. The 2–4 feet resolution panchromatic HEXAGON satellite photographs were taken 1971–1986 within the American reconnaissance programs that are better known to the scientific community for their lower-resolution CORONA images. Our aim is to evaluate the potential of combining historical CORONA and HEXAGON with recent WorldView VHRS imagery for retrospective woodland change mapping on the tree level. We mapped all trees on 30 1-ha test sites in open-canopy argan woodlands in Morocco in the field and from the VHRS imagery for estimating changes of tree density and size between 1967/1972 and 2018. Prior to image interpretation, we used simulations based on unmanned aerial system (UAS) imagery for exemplarily examining the role of illumination, viewing geometry and image resolution on the appearance of trees and their shadows in the historical panchromatic images. We show that understanding these parameters is imperative for correct detection and size-estimation of tree crowns. Our results confirm that tree maps derived solely from VHRS image analysis generally underestimate the number of small trees and trees in clumped-canopy groups. Nevertheless, HEXAGON images compare remarkably well with WorldView images and have much higher tree-mapping potential than CORONA. By classifying the trees in three sizes, we were able to measure tree-cover changes on an ordinal scale. Although we found no clear trend of forest degradation or recovery, our argan forest sites show varying patterns of change, which are further analysed in Part B of our study. We conclude that the HEXAGON stereo-panoramic camera images, of which 670,000 worldwide will soon be available, open exciting opportunities for retrospective monitoring of trees in open-canopy conditions and other woody vegetation patterns back into the 1980s and 1970s.

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Section: Small-format Aerial Photography (Sfap) Taken With An Unmanne...mentioning

confidence: 99%

Monitoring Dryland Trees With Remote Sensing. Part A: Beyond CORONA—Historical HEXAGON Satellite Imagery as a New Data Source for Mapping Open-Canopy Woodlands on the Tree Level

Marzolff

Kirchhoff

Stephan

et al. 2022

Front. Environ. Sci.

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“…A recent review concluded existing aboveground biomass products are almost entirely inconsistent across dry forests, savannas, and grasslands (Zhang et al, 2019b). Uncertainties arise from insufficient data on non-forest vegetation for calibration and validation as well as the insensitivity of remotely sensed observations to low biomass ecosystems (Duncanson et al, 2019;Cunliffe et al, 2021). Furthermore, comparisons between LSM predictions and AGC maps are strongly influenced by root-shoot ratios.…”

Section: Aboveground Biomass Carbonmentioning

confidence: 99%

Assessing Model Predictions of Carbon Dynamics in Global Drylands

Fawcett

Cunliffe

Sitch

et al. 2022

Front. Environ. Sci.

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Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO2 enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle.

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“…Remote sensing from unmanned aerial vehicles (UAVs) provides high-resolution imagery (sub-centimeter to several meters) at landscape scales and has emerged as a natural "bridge" between highly detailed but spatially sparse field measurements and coarse resolution but spatially extensive satellite remote sensing (Poley and McDermid 2020;Riihimäki et al 2019;Siewert and Olofsson 2020). UAVs show promise for measuring structural traits, such as vegetation height and biomass (Cunliffe et al 2021;Poley and McDermid 2020), especially in tundra ecosystems (Alonzo et al 2020;Cunliffe et al 2021;Fraser et al 2016). Capable UAV platforms are now reasonably priced ($1600 + USD) and can be outfitted with a variety of sensors: high-resolution RGB, multispectral, hyperspectral, thermal, and even lidar (light detection and ranging).…”

Section: Introductionmentioning

confidence: 99%

“…Structure from Motion (SfM) is emerging as a cost-effective method for capturing vegetation structure (Alonzo et al 2020;Cunliffe et al 2021). SfM works by identifying matching features in overlapping images and triangulating these features to create three-dimensional reconstructions.…”

Section: Introductionmentioning

confidence: 99%

Mapping tundra ecosystem plant functional type cover, height and aboveground biomass in Alaska and northwest Canada using unmanned aerial vehicles

et al. 2022

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Arctic vegetation communities are rapidly changing with climate warming, which impacts wildlife, carbon cycling and climate feedbacks. Accurately monitoring vegetation change is thus crucial, but scale mismatches between field and satellite-based monitoring cause challenges. Remote sensing from unmanned aerial vehicles (UAVs) has emerged as a bridge between field data and satellite-based mapping. We assess the viability of using high resolution UAV imagery and UAV-derived Structure from Motion (SfM) to predict cover, height and aboveground biomass (henceforth biomass) of Arctic plant functional types (PFTs) across a range of vegetation community types. We classified imagery by PFT, estimated cover and height, and modeled biomass from UAV-derived volume estimates. Predicted values were compared to field estimates to assess results. Cover was estimated with root-mean-square error (RMSE) 6.29-14.2% and height was estimated with RMSE 3.29-10.5 cm, depending on the PFT. Total aboveground biomass was predicted with RMSE 220.5 g m<sup>-2</sup>, and per-PFT RMSE ranged from 17.14-164.3 g m<sup>-2</sup>. Deciduous and evergreen shrub biomass was predicted most accurately, followed by lichen, graminoid, and forb biomass. Our results demonstrate the effectiveness of using UAVs to map PFT biomass, which provides a link towards improved mapping of PFTs across large areas using earth observation satellite imagery.

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Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

Abstract: Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are

Cited by 17 publications

References 74 publications

Monitoring Dryland Trees With Remote Sensing. Part A: Beyond CORONA—Historical HEXAGON Satellite Imagery as a New Data Source for Mapping Open-Canopy Woodlands on the Tree Level

Monitoring Dryland Trees With Remote Sensing. Part A: Beyond CORONA—Historical HEXAGON Satellite Imagery as a New Data Source for Mapping Open-Canopy Woodlands on the Tree Level

Assessing Model Predictions of Carbon Dynamics in Global Drylands

Mapping tundra ecosystem plant functional type cover, height and aboveground biomass in Alaska and northwest Canada using unmanned aerial vehicles

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