From UAV to PlanetScope: Upscaling fractional cover of an invasive species Rosa rugosa

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 336, P. 117693 - 117693

Published: March 11, 2023

Invasive plant species pose a direct threat to biodiversity and ecosystem services. Among these, Rosa rugosa has had severe impact on Baltic coastal ecosystems in recent decades. Accurate mapping monitoring tools are essential quantify the location spatial extent of invasive support eradication programs. In this paper we combined RGB images obtained using an Unoccupied Aerial Vehicle, with multispectral PlanetScope map R. at seven locations along Estonian coastline. We used RGB-based vegetation indices 3D canopy metrics combination random forest algorithm thickets, obtaining high accuracies (Sensitivity = 0.92, specificity 0.96). then presence/absence maps as training dataset predict fractional cover based derived from constellation Extreme Gradient Boosting (XGBoost). The XGBoost yielded prediction (RMSE 0.11, R2 0.70). An in-depth accuracy assessment site-specific validations revealed notable differences between study sites (highest 0.74, lowest 0.03). attribute these various stages invasion density thickets. conclusion, UAV is cost-effective method highly heterogeneous ecosystems. propose approach valuable tool extend local geographical scope assessments into wider areas regional evaluations.

Language: Английский

---

Systematic review and best practices for drone remote sensing of invasive plants

Methods in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 15(6), P. 998 - 1015

Published: May 6, 2024

Abstract Drones have emerged as a cost‐effective solution to detect and map plant invasions, offering researchers land managers flexibility in flight design, sensors data collection schedules. A systematic review of trends drone‐based image collection, processing analytical approaches is needed advance the science invasive species monitoring management improve scalability replicability. We systematically reviewed studies using drones for invasion research identify knowledge gaps, best practices path toward advancing management. devised database 33 standardized reporting parameters, coded each study those calculated descriptive statistics synthesized how these technologies are being implemented used. Trends show general increase since 2009 with bias temperate regions North America Europe. Most focused on testing validity machine learning or deep classification technique fewer modelling spread. Very few used assessing ecosystem dynamics impacts such determining environmental drivers tracking re‐emergence after disturbance. Overall, we noted lack field survey drone systems, analyses, which hinders replicability approaches. Based findings, develop standard framework applications foster cross‐study comparability reproducibility. suggest several areas use including (1) utilizing frameworks facilitate scientific practices, (2) integrating satellite imagery scale up relationships over larger areas, (3) an alternative in‐person ground surveys (4) leveraging assess community trait shifts tied fitness reproduction.

Language: Английский

---

Remote Sensing and Invasive Plants in Coastal Ecosystems: What We Know So Far and Future Prospects

Land, Journal Year: 2023, Volume and Issue: 12(2), P. 341 - 341

Published: Jan. 27, 2023

Coastal environments are highly threatened by invasive alien plants (IAP), and Remote Sensing (RS) may offer a sound support for IAP detection mapping. There is still need an overview of the progress extent RS applications on invaded coasts that can help development better procedures to management. We conducted systematic literature review 68 research papers implementing, recommending, or discussing tools mapping in coastal environments, published from 2000 2021. According this review, most was done China USA, with Sporobolus (17.3%) being studied genus. The number studies increased at accelerated rate 2015 onwards, coinciding transition invasion modeling. used platforms 2000s were aircraft, satellites 2005 unmanned aerial vehicles after 2014. Frequentist inference adopted classification approach 2000s, as machine learning 2009. vary ecosystem types across countries. has huge potential further improve monitoring. extension all world requires advanced bring together current future Earth observation data.

Language: Английский

---

Coastal Dune Invaders: Integrative Mapping of Carpobrotus sp. pl. (Aizoaceae) Using UAVs

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(2), P. 503 - 503

Published: Jan. 14, 2023

Coastal dune ecosystems are highly threatened, and one of the strongest pressures is invasive alien plants (IAPs). Mitigating negative effects IAPs requires development optimal identification mapping protocols. Remote sensing offers innovative tools that have proven to be very valuable for studying IAPs. In particular, unmanned aerial vehicles (UAVs) can promising, especially in study herbaceous species, yet research UAV application still limited. this study, we used images implement an image segmentation approach followed by machine learning classification a clonal invader (Carpobrotus sp. pl.), calibrating total 27 models. Our showed that: (a) results offered simultaneous RGB multispectral data improve prediction Carpobrotus; (b) best were obtained whole plant or its vegetative parts, while flowers was worse; (c) training area corresponding 20% adequate model building. Overall, our highlighted great potential using UAVs Carpobrotus mapping, despite some limitations imposed particular biology ecology these taxa.

Language: Английский

---

Monitoring the spatial–temporal distribution of invasive plant in urban water using deep learning and remote sensing technology

Ecological Indicators, Journal Year: 2024, Volume and Issue: 162, P. 112061 - 112061

Published: April 21, 2024

Despite water ecosystems being capable of sustaining biodiversity and enhancing the overall resilience urban environment, they are highly susceptible to biological invasions. Invasive aquatic plants (IAPs) threaten natural environment by reducing diversity native animal communities. Detecting IAPs mapping their distribution is crucial for protection ecosystems. This study first its kind use high-resolution unmanned aerial vehicle (UAV) imagery deep learning approaches monitor expansion Pistia stratiotes (water lettuce). A DJI Matrice 300 RTK was utilized capture time-series images with a resolution 0.018 m on Guanyin Lake, Cangshan District, Fuzhzou, China, during an outbreak subsequent rapid growth stage lettuce. Three model architectures three backbones were combined detect Model performance ability generalize evaluated determine optimal lettuce detection from UAV imagery. Results show that DeepLabv3 + ResNet-34 achieved superior in detecting imagery, yielding average accuracy 90.24 % (85.33 %≤F1_score ≤ 96.54 %) five different dates. For image acquired September 26th, U-Net ResNet-18 yielded highest (F1_score = 92.46 %), but it not multi-temporal The can have large variations at times, change rate 49.50 every two days up 60.33 %. demonstrates combination achieve excellent monitoring provide method map dynamic systems over time.

Language: Английский

---

A standard procedure for dune mapping along the Bulgarian Black Sea coast: an integrated approach combining UAS photogrammetry, geomorphological and phytocoenological surveys

Frontiers in Marine Science, Journal Year: 2025, Volume and Issue: 12

Published: May 15, 2025

Coastal dunes (CD) are dynamic environments shaped by sediment accumulation, sea breeze and vegetation cover, which also highly sensitive to human intervention. The urbanization of coastal areas, global warming rising levels pose significant threats CD systems, leading erosion habitat loss. In the past decade, total area in Bulgaria has decreased over 12 hectares, resulting complete loss five dune systems. Over 5% CDs along Bulgarian Black Sea Coast (BBSC) face similar challenges, primarily due human-induced pressure alterations landforms. This study introduces a Standard Dune Mapping Procedure (SDMP) for BBSC based on geospatial data habitats, facilitating cadastral maps registers effective conservation management activities. proposed methodology, developed through collaboration Ministry Environment Water Republic Bulgaria, Institute Oceanology Biodiversity Ecosystem Research at Academy Sciences, is multidisciplinary approach that integrates remote sensing, geomorphological, geological phytocoenological surveys analysis GIS environment. procedure involves seven stages: initial inventory collection processing, classification, high-resolution mapping habitats. SDMP aims support sustainable ecosystems emphasizing low-cost, non-intrusive sensing techniques. A pilot application “Kavatsi” system (Sozopol Municipality, Burgas District) validates SDMP’s effectiveness addressing challenges maintenance anthropogenic impact. comprehensive ensures accurate supports development practices ecosystems. offers step forward systematic responding urgent need strategies degradation thus plays crucial role CDs.

Language: Английский

---

Assessing the Efficacy of Phenological Spectral Differences to Detect Invasive Alien Acacia dealbata Using Sentinel-2 Data in Southern Europe

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(3), P. 722 - 722

Published: Jan. 26, 2023

Invasive alien plants are transforming the landscapes, threatening most vulnerable elements of local biodiversity across globe. The monitoring invasive species is paramount for minimizing impact on biodiversity. In this study, we aim to discriminate and identify spatial extent Acacia dealbata Link from other using RGB-NIR Sentinel-2 data based phenological spectral peak differences. Time series were processed Earth Engine platform random forest importance was used select suitable derived metrics. Thereafter, a machine learning algorithm trained between A. native species. A flowering period detected in March metrics difference blooming pre (January) or post (May) months highly discrimination. best-fitted classification model shows an overall accuracy 94%, including six We find that 55% presences widely widespread patches replacing Pinus pinaster Ait. stands. This also creates continuous monospecific stands representing 33% presences. approach demonstrates its value detecting mapping bands differences providing information early detection improve sustainable management.

Language: Английский

---

Cross-taxon analysis in the highly threatened Mediterranean dunes reveals consistent diversity patterns in butterfly and plant communities

Biodiversity and Conservation, Journal Year: 2024, Volume and Issue: 33(13), P. 3643 - 3661

Published: Aug. 16, 2024

Abstract Butterflies and plant species are widely used as model systems in biodiversity conservation research. However, little is known about spatial patterns of butterfly diversity linked to communities across coastal dune ecotones. We explored the relation between vegetation a Mediterranean protected system Central Italy. sampled on shifting fixed dunes investigated their distribution by indexes Species Abundance Diversity models (SADs). also computed beta-diversity analyzed correlation analyses. Cross-taxon congruence richness, composition abundance was assessed using Mantel tests. Both were higher than dunes. In both communities, SADs adequately described geometric series model, which typical harsh environments with simple dominated few species. Among butterflies plants, we identified found only either or Correlation for entomophilous more abundant anemophilous ones. Our results indicate that respond sea-inland environmental gradient, forming distinct specialized taxa. findings provide evidence importance butterfly-plant relations preserving biological ecosystem functioning areas.

Language: Английский

---

Integrating UAV imagery and machine learning via Geographic Object Based Image Analysis (GEOBIA) for enhanced monitoring of Yucca gloriosa in Mediterranean coastal dunes

Ocean & Coastal Management, Journal Year: 2024, Volume and Issue: 258, P. 107377 - 107377

Published: Sept. 13, 2024

Language: Английский

---

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(6), P. 1331 - 1331

Published: March 9, 2022

Analyses of climate change based on point observations indicate an extension the plant growing season, which may have impact production and functioning natural ecosystems. involving remote sensing methods, added more detail to results obtained in traditional way, been carried out only since 1980s. The paper presents a bibliometric analysis papers related season published from 2000–2021 included Web Science database. Through filtering, 285 publications were selected subjected statistical processing their content. This resulted identification author teams that mostly focused research vegetation growth selection most common keywords describing beginning, end, duration season. It was found studies reported Asia, Europe, North America (i.e., 32%, 28%, respectively). analyzed articles show advantage satellite data over low-altitude ground-based providing information vegetation. Over three quarters communities. In case crops, wheat rice frequently studied plants they 30% 20% publications,

Language: Английский

---