Restoration Monitoring Research Articles

Remote sensing approaches to monitor tropical forest restoration: Current methods and future possibilities

Abstract Tropical forests are increasingly threatened by deforestation and degradation, impacting carbon storage, climate regulations and biodiversity. Restoring these ecosystems is crucial for environmental sustainability, yet monitoring these efforts poses significant challenges. Secondary forests are in a constant state of flux, with growth depending on multiple factors. Remote sensing technologies offer cost‐effective, scalable and transferable solutions, advancing forest restoration monitoring towards more accurate, efficient and real‐time data analysis and interpretation. This review provides a comprehensive evaluation of the current state and advancements in remote sensing technologies applied to monitoring tropical forest restoration. Synthesis and applications: This review brings together the state of the art of remote sensing technologies, such as very‐high‐resolution RGB imagery, multi‐ and hyperspectral imaging, lidar, radar and thermal‐infrared technologies and their applicability in monitoring forest restoration. In conclusion, this review emphasizes the potential of remote sensing technologies, coupled with advanced computational techniques, to enhance global efforts towards effective and sustainable forest restoration monitoring.

The Effect of Vegetation Ecological Restoration by Integrating Multispectral Remote Sensing and Laser Point Cloud Monitoring Technology.

This research aims to evaluate and monitor the effectiveness of vegetation ecological restoration by integrating Multispectral Remote Sensing (MRS) and laser point cloud (LPC) monitoring technologies. Traditional vegetation restoration monitoring methods often face challenges of inaccurate data and insufficient coverage, and the use of MRS or LPC techniques alone has its limitations. Therefore, to more accurately monitor the vegetation restoration status, this study proposes a new monitoring method that combines the advantages of the large-scale coverage of MRS technology and the high-precision three-dimensional structural data analysis capability of LPC technology. This new method was applied in the Daqing oilfield area of China, aiming to provide effective ecological restoration assessment methods through the precise monitoring and analysis of regional vegetation growth and coverage. The results showed that there was a negative correlation between the vegetation humidity index and vegetation growth in the Daqing oilfield in 2023. The estimated monitoring effect of the research method could reach over 90%, and the coverage area of hydrangea restoration in the monitoring year increased by 7509 km2. The research technology was closer to the actual coverage situation. The simulation image showed that the vegetation coverage in the area has significantly improved after returning farmland to forests. Therefore, the technical methods used can effectively monitor the ecological restoration of vegetation, which has great research significance for both vegetation restoration and monitoring.

Changes in satellite‐derived spectral variables and their linkages with vegetation changes after peatland restoration

Remote sensing (RS) can be an efficient monitoring method to assess the ecological impacts of restoration. Yet, it has been used relatively little to monitor post‐restoration changes in boreal forestry‐drained peatlands, and particularly the linkages between changes in RS and plant species remain vague. To understand this gap, we utilize data from the Finnish peatland restoration monitoring network spanning 150 sites and a 10‐year post‐restoration monitoring period. We employ Bayesian joint species distribution models (Hierarchical Modeling of Species Communities) to study (1) the changes in optical Sentinel‐2 and Landsat satellite spectral signatures, (2) whether the RS variables improve predictions of vascular plant and moss species and functional type occurrence and cover, and (3) what kinds of associations exist between RS variables and plant species or functional types. Our results show that peatland restoration increases the reflectance of red and near‐infrared (NIR) bands in sparsely treed pine mire forests and open mires but not in densely treed spruce mire forests. Impacts on other tested RS variables consisting of moisture and greenness indices are less clear. Additionally, RS variables increase species‐ or functional type‐specific predictive power only modestly, and there are few clear links between the changes in RS variables and species or functional‐type occurrence and cover. We suggest that red and NIR reflectance can be used as satellite‐based indicators for peatland restoration success and further studies are required to develop usable methods for detecting species‐specific changes with RS.

Toward the quantification of the climate co-benefits of invasive mammal eradication on islands: a scalable framework for restoration monitoring

Toward the quantification of the climate co-benefits of invasive mammal eradication on islands: a scalable framework for restoration monitoring

Stream Restoration Effects on Habitat and Abundance of Native Cutthroat Trout

ABSTRACTRestoration practitioners spend more than $1 billion each year restoring US rivers and streams but commit comparatively few resources to evaluating project effectiveness. Meanwhile, monitoring and disseminating the outcomes of restoration projects remains our best opportunity to learn from past successes and failures and to, ultimately, improve the cost effectiveness of restoration. We monitored the physical and biological outcomes of a stream restoration project in the Rocky Mountains, the goals of which were to improve habitat for and productivity of native Colorado River Cutthroat Trout (CRCT) and the scope of which included three contiguous reaches under different restoration treatments. Moreover, we evaluated the efficacy of the restoration project relative to its stated goals and objectives. To test for restoration effects on physical and biological indicators we coupled a before‐after, control‐impact (BACI) study design with (generalized) linear mixed models. Over the course of 7 years, we detected restoration‐related increases in floodplain connectivity, streambank stability, and riparian shrub cover, as well as decreases in summer stream temperature. Despite measured improvements in native trout habitat, we detected no evidence of a restoration effect on density or biomass of age‐1 and older CRCT. Although our study was somewhat limited in scope, our findings contribute toward a relatively small body of work on monitoring and effectiveness of river restoration.

Soundscape analysis can be an effective tool in assessing seagrass restoration early success

Restoration of vulnerable marine habitats is becoming increasingly popular to cope with widespread habitat loss and the resulting decline in biodiversity and ecosystem services. Lately, restoration strategies have been employed to enhance the recovery of degraded meadows of the Mediterranean endemic seagrass Posidonia oceanica. Typically, habitat restoration success is evaluated by the persistence of foundation species after transplantation (e.g., plant survival and growth) on the short and long-term, although successful plant responses do not necessarily reflect the recovery of ecosystem biodiversity and functions. Recently, soundscape (the spatial, temporal and frequency attribute of ambient sound and types of sound sources characterizing it) has been related to different habitat conditions and community structures. Thus, a successful restoration action should lead to acoustic restoration and soundscape ecology could represent an important component of restoration monitoring, leading to assess successful habitat and community restoration. Here, we evaluated acoustic community and metrics in a P. oceanica restored meadow and tested whether the plant transplant effectiveness after one year was accompanied by a restored soundscape. With this goal, acoustic recordings from degraded, transplanted and reference meadows were collected in Sardinia (Italy) using passive acoustic monitoring devices. Soundscape at each meadow type was examined using both spectral analysis and classification of fish calls based on a catalogue of fish sounds from the Mediterranean Sea. Seven different fish sounds were recorded: most of them were present in the reference and transplanted meadows and were associated to Sciaena umbra and Scorpaena spp. Sound Pressure Level (SPL, in dB re: 1 μPa-rms) and Acoustic Complexity Index (ACI) were influenced by the meadow type. Particularly higher values were associated to the transplanted meadow. SPL and ACI calculated in the 200–2000 Hz frequency band were also related to high abundance of fish sounds (chorus). These results showed that meadow restoration may lead to the recovery of soundscape and the associated community, suggesting that short term acoustic monitoring can provide complementary information to evaluate seagrass restoration success.

Predicting 3D and 2D surface area of corals from simple field measurements

The structural architecture of coral reefs is a known predictor of species richness, fish biomass and reef resilience. At a smaller scale, three-dimensional (3D) surface area of corals is a fundamental determinant of physical and biological processes. Quantifying the 3D surface area of corals has applications for a broad range of scientific disciplines, including carbonate production estimates, coral predation studies, and assessments of reef growth. Here, we present morphotaxon-specific conversion metrics to estimate total 3D surface area and projected 2D surface area of individual colonies from simple field measurements of colony maximum diameter. Underwater photogrammetry techniques were used to quantify surface area and estimate conversion metrics. Bayesian models showed strong non-linear (power) relationships between colony maximum diameter and both total 3D surface area and projected 2D surface area for 13 out of 15 morphotaxa. This study presents a highly resolved and efficient method for obtaining critical surface area assessments of corals for various applications, including assessments of biotic surface area, tissue biomass, calcification rates, coral demographic rates, and reef restoration monitoring.

Monitoring invasive exotic grass species in ecological restoration areas of the Brazilian savanna using UAV images

Identifying and monitoring invasive exotic grasses (IEG) is critical for the ecological restoration of grasslands and savannas, as they are the main barrier to the successful recovery of native grasslands and savannas. The integration of high-resolution remote sensing data, acquired through UAVs (Unmanned Aerial Vehicles), with machine learning algorithms is advancing restoration monitoring. The present study aimed to estimate IEG cover and identify plots with different invasive species dominance in ecological restoration areas in the Brazilian savanna. For ground truth, species cover estimates were carried out in plots through point-line intercept sampling. Then, the areas were classified according to the dominance of each invasive species (>40% vegetation cover) or of a mix of native species. A multispectral camera onboard a UAV was used to acquire images in the visible to near-infrared spectrum. From the images, vegetation indices and texture metrics were derived as predictor variables. The Random Forest (RF) algorithm was used to estimate the percentage of invasive species cover and to classify plots in terms of species dominance. The final RF regression for invasive species cover percentage presented an R2 of 0.71 and selected the blue band, NIR and Ratio Vegetation Index (RVI) as the most important variables. The overall accuracy of plot classification according to species dominance was 84%. The most prominent predictors were the Green Chlorophyll Index (GCI), the atmospherically resistant vegetation index (ARVI), and the RVI. The structural and photosynthetic characteristics of exotic and native species influenced the spectral responses. In conclusion, multispectral images acquired with UAV can be used to estimate the proportion of invasion in restoration sites and to map areas dominated by different invasive grass species in grasslands and savannas. This is a useful tool for evaluating restoration success and can help indicate areas that require management interventions.

Comparing airborne and terrestrial LiDAR with ground-based inventory metrics of vegetation structural complexity in oil palm agroforests

Vegetation structural complexity is an important component of forest ecosystems, influencing biodiversity and functioning. Due to the heterogeneous distribution of vegetation elements, structural complexity underpins ecological dynamics, species composition, microclimate, and habitat diversity. Field measurements and Light Detection and Ranging (LiDAR) data, such as airborne (ALS) and terrestrial (TLS), can assess structural characteristics of forest and agroforestry systems at various spatial scales. This assessment is urgently needed for monitoring ecosystem restoration in degraded lands (e.g., in oil palm landscapes), where it is not well-known how structural measures derived from these different approaches relate to each other. Here, we compared the degree of correlation between individual and multivariate datasets of vegetation structural complexity metrics derived from ALS, TLS, and ground-based inventory approaches. The study was conducted in a 140 ha oil palm monoculture, enriched with 52 plots in the form of tree islands representing agroforestry systems of varying sizes and planted diversity levels in Sumatra, Indonesia. Our datasets comprised 25 ALS, five TLS, and nine ground-based inventory metrics. We studied correlations among metrics related to traditional stand summary, heterogeneity, and vertical and horizontal stand structure. We used principal component analysis for data dimensionality reduction, correlation analysis to quantify the strength of relationships between metrics, and Procrustes analysis to investigate the agreement between datasets. Significant correlations were found between ALS and TLS metrics for canopy density (r = 0.79) and maximum tree height (r = 0.58) and between ALS and ground-based inventory measures of stand heterogeneity and height diversity (r between 0.60 and −0.63). Further, we observed significant agreements between the ordinations of multivariate datasets (r = 0.56 for ALS − TLS; and r = 0.46 for ALS – ground-based inventory). Our findings underline the ability of ALS to capture structural complexity patterns, especially for canopy gap dynamics and vegetation height metrics, as captured by TLS, and for measures of heterogeneity and vertical structure as captured by ground-based inventories. Our study highlights the strength of each approach and underscores the potential of integrating ALS and TLS with ground-based inventories for a comprehensive characterization of vegetation structure in complex agroforestry systems, which can provide guidance for their management and support ecosystem restoration monitoring efforts.

Integrating Future Multi-Scenarios to Evaluate the Effectiveness of Ecological Restoration: A Case Study of the Yellow River Basin

Ecological restoration is an important strategy for mitigating environmental degradation, and the effectiveness evaluation of ecological restoration is of profound significance for the scientific implementation of restoration projects. This study improved the Patch-generating Land Use Simulation (PLUS) model. It was used to simulate the land use patterns under multi-scenarios such as natural development (ND), economic priority (EP), and ecological restoration (ER) in 2030. An evaluation framework covering ecological “Restoration–Monitoring–Effectiveness” (RME) was proposed. Based on 30 m high-resolution remote-sensing data from 2000 to 2020, the land use distribution, landscape pattern changes, and ecosystem services under different scenarios were evaluated and predicted in the Yellow River Basin of Sichuan to verify the effectiveness of the evaluation framework. The results showed the following: (1) Under the ER scenario, the transfer of land use types in 2020–2030 was mainly characterized by an increase in the area of wetlands and a decrease in the area of built-up land. (2) There were obvious differences in land use and landscape patterns under different scenarios. Compared with the ND and EP scenarios, the growth of the construction rate was suppressed in the ER scenario, and the coverage of grassland and wetlands increased significantly. (3) The mean values of ecosystem services in the ER scenario were higher than those in the ND and EP scenarios. These findings clearly indicate that the RME evaluation system can accurately evaluate the ecological restoration effects under multi-scenarios in the future, providing a new perspective for ecological restoration evaluation in other regions.

Evaluating the Effect of Common Carp Control on Restoration of a Coastal Wetland in the Laurentian Great Lakes

Great Lakes coastal wetlands are under considerable stress from numerous anthropogenic threats, including the introduction of invasive species. Common Carp, an invasive species in North America, has been well documented as an influential wetland stressor. This study documents the impact of Common Carp reintroduction on a restored wetland fish community and abiotic and vegetation variables. Oshawa Second Marsh was restored using an exclusion berm with a fish grate and manual water-level drawdown to re-establish vegetation. Five years into restoration monitoring, Common Carp regained access to the wetland after the fish grate was vandalized. Fish community health was monitored over time using multimetric and multivariate approaches based on abiotic and vegetation variables. Improvements in fish community health were observed during restoration monitoring, but after Common Carp reintroduction, fish community health decreased and the community homogenized. Seven of the ten abiotic and vegetation variables monitored changed significantly after Common Carp reintroduction. This study highlights the impact that Common Carp has on the functional integrity of coastal wetlands and the significance of its management for restoration.

Beta diversity of restored river dike grasslands is strongly influenced by uncontrolled spatio‐temporal variability

AbstractAimsUnderstanding the spatio‐temporal patterns of restoration outcomes is crucial to improve predictability of restoration. High beta diversity of species‐rich communities is sought because it increases overall biodiversity and improves ecosystem stability and multifunctionality. For predictive restoration, it is important to identify the significance of drivers like site characteristics but also uncontrolled factors such as spatial effects, historical factors, and year effects.LocationDikes at river Danube, SE Germany.MethodsWe studied dike grasslands 4–19 years after restoration over five years (2017–2021, 41 plots in 12 sites). We calculated beta diversity indices to describe spatial variation and temporal turnover, including their additive components ‘replacement’ and ‘nestedness’, or ‘gains’ and ‘losses’. We analysed the main drivers of beta diversity like local site characteristics, landscape, and historical factors.ResultsSpatial variation of the restored dike grasslands was dominated by the replacement component and showed no homogenisation despite a significant temporal turnover. The replacement drivers changed over time, although replacement was mainly affected by slope aspect and landscape factors. Historical factors were inconsistent over time, and no statistically clear drivers of nestedness were found. The dike grasslands exhibited a year‐to‐year turnover in species composition of 37 ± 11%. Gains and losses were balanced over time, although the ratio changed and was most pronounced on south‐facing slopes.ConclusionsThe restored grasslands exhibited spatial variation by site characteristics but also by spatial factors which were not controlled by restorations. Moreover, high non‐directional temporal turnover occurred, caused most likely by weather fluctuations, slightly varying management, and stochastic biotic dynamics. Thus, flexible targets are recommended for restoration monitoring, by defining a set of desired states within a certain range. Furthermore, the dominance of the replacement component of spatial variation should move the focus from defining one precise restoration approach to defining a set of possible methods which together would foster beta diversity.

Remote Sensing Application in Ecological Restoration Monitoring: A Systematic Review

In the context of the continuous degradation of the global environment, ecological restoration has become a primary task in global environmental governance. In this process, remote sensing technology, as an advanced monitoring and analysis tool, plays a key role in monitoring ecological restoration. This article reviews the application of remote sensing technology in ecological restoration monitoring. Based on a comprehensive analysis of the literature in the field of ecological remote sensing, it systematically summarizes the major in-orbit spaceborne and airborne sensors and their related products. This article further proposes a series of evaluation indicators for ecological restoration from four aspects: forests, soil, water, and the atmosphere, and elaborates on the calculation methods for these indicators. In addition, this paper also summarizes the methods for evaluating the effectiveness of ecological restoration, including subjective evaluation, objective evaluation, and comprehensive evaluation methods. Finally, we analyze the challenges faced by remote sensing technology in evaluating ecological restoration effectiveness, such as issues with the precision of indicators extraction, the limitations of spatial resolution, and the diversity of evaluation methods. This review also looks forward to future ecological restoration technologies, such as the potential applications of integrated aerospace and terrestrial remote sensing, multi-data fusion, and machine learning technologies. This study reveals the effectiveness of remote sensing technology in ecological restoration monitoring, aiming to provide efficient tools and innovative strategies for future remote sensing monitoring and assessment of ecological restoration.

Evaluating stakeholder perceptions on drone use in forest restoration using a social–ecological systems framework

Abstract Forest restoration is critical for meeting global objectives related to climate change mitigation, biodiversity conservation and sustainable livelihoods. Recently, new technologies such as unmanned aerial vehicles (hereafter drones) have been promoted to support activities across the planning, implementation, monitoring and maintenance stages of forest restoration. Yet, there is little empirical data on how the development and application of drones are perceived by restoration managers and stakeholders and how drones intersect with existing forest social–ecological systems (SESs). Here, we investigate how drone tree planting initiatives in Australia can support ecosystem restoration. Through interviews and focus groups with key actors, we examine the opportunities and challenges that have been experienced or are foreseen with drone use. Opportunities included the ability of drones to access degraded sites that are difficult or unsafe to access on foot, for example, following bushfires, floods or landslides. They were also perceived to ease the labour shortage of bush regenerators in Australia. Drones were considered particularly useful when operating at scales of around 20–100 ha. Challenges included restrictive flying regulations that prohibit use of artificial intelligence to plot courses through complex terrain, their unproven ability to control or eradicate weeds and the uncertain supply, germination and survival rates of seeds—upon which drone‐based restoration relies. Drone use may also reduce the emotional, spiritual and cultural connections of people to the land, as compared to hand‐planting seeds or seedlings. We conclude by conceptualising how drone‐assisted restoration can be embedded within a forest SESs management framework. Ultimately, we argue that drones offer a ‘boutique’ restoration approach that supports, rather than replaces, traditional forest restoration techniques. Read the free Plain Language Summary for this article on the Journal blog.

Using a novel vector length stability index (VLSI) to evaluate soil aggregate stability: A preliminary study

Soil aggregate stability is an important soil characteristic which can represent the improvement of soil structure after revegetation. Due to the high heterogeneity of soil, large-scale sampling is usually necessary to estimate the spatial variation of aggregate stability across landscapes. Although there are many methods and corresponding indices for analysis of aggregate stability, many of them are not suitable for investigations with a large number of samples due to time-consuming experimental practices. To avoid unnecessary costs of time and labor in the long-term land degradation and restoration monitoring across large regional scales, simple indices of aggregate stability would help monitoring across large regional scales. For this reason, we introduced a new, simple, and normalized index, the vector length stability index (VLSI) and its weighted form (wVLSI) to describe soil aggregate stability. The VLSI shares key information of aggregate size distribution with mean weight diameter (MWD), but it is naturally normalized and dimensionless. This new index was tentatively tested to describe soil aggregate stability of the 0–30 cm soil layers under artificial plantations, natural grassland, abandoned farmland, and farmland in production in a small watershed located in the Loess Plateau of China. The results showed that the aggregate stability of the 0–20 cm layers in abandoned farmland could be recovered near to the condition under artificial plantations just after 2-year abandonment, but the aggregate stability hardly changed in the 20–30 cm layer. The aggregate stability of the 0–10 cm layer in natural recovered grassland is close to that in top soil layers under artificial plantations, but the stability in the 10–30 layers appeared as low as that in farmland. Because of its simple form and low data requirements, the VLSI could be an alternative efficient tool for soil aggregate stability evaluation when a large number of samples are needed.

Review and assessment of smartphone apps for forest restoration monitoring

With increased interest in forest restoration comes an urgent need to provide accurate, scalable, and cost‐effective monitoring tools. The ubiquity of smartphones has led to a surge in monitoring apps. We reviewed and assessed monitoring apps found through web searches and conversations with practitioners. We identified 42 apps that (1) automatically monitor indicators or (2) facilitate data entry. We selected the five most promising from the first category, based on their relevance, availability, stability, and user support. We compared them to traditional field techniques in a well‐studied restoration project in Costa Rica. We received further feedback from 15 collaborator organizations that evaluated these in their corresponding field restoration sites. Diameter measurements correlated well with traditional tape‐based measurements (R2 = 0.86–0.89). Canopy openness and ground cover showed weaker correlations to densiometer and quadrat cover measurements (R2 = 0.42–0.51). Apps did not improve labor efficiency but do preclude the purchase of specialized field equipment. The apps reviewed here need further development and validation to support monitoring adequately, especially in the tropics. Estimates of development and maintenance costs, as well as statistics on user uptake, are required for cost‐effective development. We recommend a coordinated effort to develop dedicated restoration monitoring apps that can speed up and standardize the collection of indicators and provide evidence on restoration outcomes alongside a centralized repository of this information.

Evaluating effectiveness of restoration to address current stressors to riverine fish

Abstract River restoration programmes with the goal of conserving and rehabilitating inland fishes have a multi‐decadal history, but evaluation and synthesis of past restoration actions have been limited by a lack of monitoring and reporting. Given that calls for both monitoring and systematic reviews of restoration have increased, we were interested in the influence that restoration has had on improving conditions for riverine fishes resulting from long‐standing and increasingly prominent stressors. Our objectives were to (1) identify which stressors were targeted in river restoration efforts, (2) determine the proportion of published studies that articulate restoration goals and develop comparative monitoring designs for assessing the effects of restoration on fishes, and (3) conduct a meta‐analysis to synthesise fish responses to restoration projects. We assessed restoration effectiveness for increasing fish density and richness from peer‐reviewed papers published over the past decade using a global systematic review and meta‐analysis. We found that restoration actions addressed major stressors primarily by improving in‐stream habitat (37%), increasing in‐stream longitudinal connectivity (26%) and increasing lateral floodplain connections (9%). Although 81% of studies had comparative monitoring designs (i.e., before/after and control/impact) and stated restoration goals, only 40% of those studies reported sufficient data to be included in the meta‐analysis. Projects which increased in‐stream connectivity had the largest positive effect size on fish density and richness compared to in‐stream habitat improvements and increasing floodplain connections. Time since restoration and restoration size (i.e., geographical footprint) were not strong predictors of fish response effect sizes. Restoration effectiveness was highly variable among project types. Authors of studies included in the meta‐analysis often identified spatial or temporal scale of monitoring, overriding catchment conditions, and recolonisation potential as sources of variability and effectiveness in restoration outcomes. Systematic reporting of these and other covariates may help guide processes in restoration evaluation and provide valuable research insights. Despite increased emphasis on monitoring, incomplete data reporting limited the number of studies that could be included for quantitative meta‐analysis. Persistent emphasis on setting specific criteria (e.g., measurable outcomes of fish response) for restoration goals, project monitoring, data reporting, information sharing and collaborative projects is likely to continue to improve understanding of restoration effectiveness transferable to future endeavours. Our results can be used to support river restoration practitioners with evidence‐based information to evaluate the cost–benefit ratio of competing restoration priorities, and inform restoration planning and implementation for riverine fish.

Unmanned Aerial Vehicle (UAV)-Based Vegetation Restoration Monitoring in Coal Waste Dumps after Reclamation

Frequent spontaneous combustion activities restrict ecological restoration of coal waste dumps after reclamation. Effective monitoring of vegetation restoration is important for ensuring land reclamation success and preserving the ecological environment in mining areas. Development of unmanned aerial vehicle (UAV) technology has enabled fine-scale vegetation monitoring. In this study, we focused on Medicago sativa L. (alfalfa), a representative herbaceous vegetation type, in a coal waste dump after reclamation in Shanxi province, China. The alfalfa aboveground biomass (AGB) was used as an indicator for assessing vegetation restoration. The objective of this study was to evaluate the capacity of UAV-based fusion of RGB, multispectral, and thermal infrared information for estimating alfalfa AGB using various regression models, including random forest regression (RFR), gradient boosting decision tree (GBDT), K-nearest neighbor (KNN), support vector regression (SVR), and stacking models. The main results are as follows: (i) UAV multi-source data fusion improved alfalfa AGB estimation accuracy, although the enhancement diminished with the increasing number of sensor types. (ii) The stacking model consistently outperformed RFR, GBDT, KNN, and SVR regression models across all feature fusion combinations. It achieved high accuracy with R2 of 0.86–0.88, RMSE of 80.06–86.87 g/m2, and MAE of 60.24–62.69 g/m2. Notably, the stacking model based on only RGB imagery features mitigated the accuracy loss from limited types of features, potentially reducing equipment costs. This study demonstrated the potential of UAV in improving vegetation restoration management of coal waste dumps after reclamation.

Performance and accuracy of cross‐section tracking methods for hydromorphological habitat assessment in wadable rivers with sparse canopy conditions

AbstractThis article investigates the performance and accuracy of continuous Real‐Time Kinematic (RTK) Global Navigation Satellite System (GNSS) position tracking for hydromorphological surveys, based on a comprehensive river restoration monitoring campaign. The aim of the research was to assess the method's suitability for efficient data collection in turbid, wadable rivers with sparse canopy conditions, and responds to the water management sector's increasing demand for efficient, low‐cost, and robust survey techniques. The methodological approach involved comparing manual, cross‐sectional water depth measurements to water depth estimations obtained by applying different interpolation methods to the continuous tracking data. The results demonstrate good agreement between both datasets (R2 = 0.77, RMSE = 0.13 m). When using a local standard deviation filter to remove noisy RTK‐GNSS measurements, estimation performance increased significantly (R2 = 0.96, RMSE = 0.06 m). The filter's influence on the hydromorphological habitat statistics mean water depth and coefficient of variation was limited but proved to be relevant for reach‐scale assessments of hydromorphological diversity. Based on a correlation analysis of >106 RTK‐GNSS position logs, we furthermore assessed the impact of tree canopy on RTK‐GNSS measurement accuracy and observed a strong influence within 6.5 m from the canopy border. Estimated accuracy deteriorated noticeably when canopy penetration exceeded 1 m, and accuracies >1 m were common beyond 4 m penetration. The study highlights the efficiency gains achieved with RTK‐GNSS tracking, and showcases its potential for hydromorphological surveys and streamgaging applications in challenging conditions, making it a promising alternative to traditional methods and remote sensing techniques.

Peatland restoration in Norway – evaluation of ongoing monitoring and identification of plant indicators of restoration success

Norway launched a national action plan on wetland restoration in 2016. So far, 90% of the restoration effort has been on peatland restoration, with about 140 mires restored so far. There are three main restoration goals stated in the action plan: 1) limit greenhouse gas (GHG) emission, 2) climate adaptation and 3) improved ecological condition. Quantifying the outcome of the restoration actions is necessary to evaluate whether the goals of the action plan are met. A vegetation monitoring protocol was suggested before restoration started and has been implemented at five restoration sites. As the peatland restoration effort in Norway is increasing, it is timely to evaluate if the data currently collected can measure peatland restoration outcome. We evaluate the monitoring protocol based on statistical analyses of the data collected at two sites, describe how indicator species can be identified using generalized composition data used as the basis for classifying habitats in Norway (EcoSyst framework), and suggest the way forward for peatland restoration monitoring in Norway. Data collected according to the monitoring protocol can document changes in species composition at restoration sites, but has limitations when the ecological complexity at the sites increases and reference sites are unavailable. We argue that adjusting the monitoring protocol will: 1) facilitate alignment with existing peatland research; 2) connect better with monitoring programs where data is collected applying EcoSyst framework principles; and 3) enable upscaling to cover the wide variation emerging in peatland restoration.