UAV-Based forest health monitoring : a systematic review

CITATION: Ecke, S. et al. 2022. UAV-Based forest health monitoring : a systematic review. Remote Sensing, 14(13):3205, doi:10.3390/rs14133205.The original publication is available at https://www.mdpi.comIn recent years, technological advances have led to the increasing use of unmanned aerial vehicles (UAVs) for forestry applications. One emerging field for drone application is forest health monitoring (FHM). Common approaches for FHM involve small-scale resource-extensive fieldwork combined with traditional remote sensing platforms. However, the highly dynamic nature of forests requires timely and repetitive data acquisition, often at very high spatial resolution, where conventional remote sensing techniques reach the limits of feasibility. UAVs have shown that they can meet the demands of flexible operation and high spatial resolution. This is also reflected in a rapidly growing number of publications using drones to study forest health. Only a few reviews exist which do not cover the whole research history of UAV-based FHM. Since a comprehensive review is becoming critical to identify research gaps, trends, and drawbacks, we offer a systematic analysis of 99 papers covering the last ten years of research related to UAV-based monitoring of forests threatened by biotic and abiotic stressors. Advances in drone technology are being rapidly adopted and put into practice, further improving the economical use of UAVs. Despite the many advantages of UAVs, such as their flexibility, relatively low costs, and the possibility to fly below cloud cover, we also identified some shortcomings: (1) multitemporal and long-term monitoring of forests is clearly underrepresented; (2) the rare use of hyperspectral and LiDAR sensors must drastically increase; (3) complementary data from other RS sources are not sufficiently being exploited; (4) a lack of standardized workflows poses a problem to ensure data uniformity; (5) complex machine learning algorithms and workflows obscure interpretability and hinders widespread adoption; (6) the data pipeline from acquisition to final analysis often relies on commercial software at the expense of open-source tools.https://www.mdpi.com/2072-4292/14/13/3205Publisher's versio

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Movement and habitat use of the pool frog (Pelophylax lessonae) in Sweden: gaining ecological insights to improve forest management practices

The pool frog (Pelophylax lessonae) has a limited distribution in Scandinavia and is red-listed in Sweden. Most of the ~120 Swedish localities are concentrated along a limited coastline in south-central Sweden. The major threat to the species is loss of suitable habitat, e.g. due to forest drainage ditching and clear cutting. Understanding important pathways between local subpopulations (ponds) is important for conservation and landscape management. To improve forest management practices around populated ponds, knowledge on habitats used for dispersal and hibernation is crucial. We conducted a landscape connectivity analysis for the main region of the Swedish populations, based on presence/absence data on populated ponds from a survey in 2009; and a cost raster based on habitat data, forest data and a wetness index. To verify these theoretical dispersal routes, we performed radio-telemetry tracking of 43 individuals around four ponds, during the summer and autumn of 2017. As most frogs did not move away from the pond, translocations 500 m into localities connected with the ponds were conducted for 20 individuals. Six individuals were followed to their hibernation sites. Home range of individuals was estimated by utilization distributions which were calculated with the assumption of biased random walks. We determined habitat use preference with GLMMs of usage/available habitat using forest data and wetness indices. Most individuals moved according to theory, in distinct moves along the wet habitat strings predicted from connectivity analysis. Translocated individuals moved quickly to suitable water bodies and remained there, often showing homing behavior. Habitat use of these individuals showed preference for open water bodies and open wetlands. Pine forests were avoided, while proximity to streams and distance from forest favored habitat usage. The theoretical dispersal routes (in low cost areas from the connectivity analysis) were used more often than high cost areas, verifying their relevance for conservation planning and landscape management. Hibernation sites were not located in burrows, as previously suggested, but instead directly in litter on the forest floor. All individuals hibernated on solid ground, within 250 meters from breeding ponds. To maintain functional connectivity we suggest that also stream networks that interconnect neighboring ponds and have low presence of pine, should be preserved as dispersal corridors. Around the breeding ponds, hibernation sites at up to 250 meters should be considered during management activities. This project exemplifies the potential of combining theoretical analyses and practical field studies to improve our understanding of the requirements of a threatened species. Furthermore, it shows how an adaptive management approach and cooperation between forestry owners and managers, authorities, nature conservation consultancies and researchers may improve management and conservation practices.peerReviewe

UAV-Based Forest Health Monitoring: A Systematic Review

In recent years, technological advances have led to the increasing use of unmanned aerial vehicles (UAVs) for forestry applications. One emerging field for drone application is forest health monitoring (FHM). Common approaches for FHM involve small-scale resource-extensive fieldwork combined with traditional remote sensing platforms. However, the highly dynamic nature of forests requires timely and repetitive data acquisition, often at very high spatial resolution, where conventional remote sensing techniques reach the limits of feasibility. UAVs have shown that they can meet the demands of flexible operation and high spatial resolution. This is also reflected in a rapidly growing number of publications using drones to study forest health. Only a few reviews exist which do not cover the whole research history of UAV-based FHM. Since a comprehensive review is becoming critical to identify research gaps, trends, and drawbacks, we offer a systematic analysis of 99 papers covering the last ten years of research related to UAV-based monitoring of forests threatened by biotic and abiotic stressors. Advances in drone technology are being rapidly adopted and put into practice, further improving the economical use of UAVs. Despite the many advantages of UAVs, such as their flexibility, relatively low costs, and the possibility to fly below cloud cover, we also identified some shortcomings: (1) multitemporal and long-term monitoring of forests is clearly underrepresented; (2) the rare use of hyperspectral and LiDAR sensors must drastically increase; (3) complementary data from other RS sources are not sufficiently being exploited; (4) a lack of standardized workflows poses a problem to ensure data uniformity; (5) complex machine learning algorithms and workflows obscure interpretability and hinders widespread adoption; (6) the data pipeline from acquisition to final analysis often relies on commercial software at the expense of open-source tools

Real-world Treatment Sequencing in Patients with Metastatic Castration-resistant Prostate Cancer: Results from the Prospective, International, Observational Prostate Cancer Registry

Background: Prostate cancer has a multifaceted treatment pattern. Evidence is lacking for optimal treatment sequences for metastatic castration-resistant prostate cancer (mCRPC). Objective: To increase the understanding of real-world treatment pathways and outcomes in patients with mCRPC. Design, setting, and participants: A prospective, noninterventional, real-world analysis of 3003 patients with mCRPC in the Prostate Cancer Registry (PCR; NCT02236637) from June 14, 2013 to July 9, 2018 was conducted. Intervention: Patients received first- and second-line hormonal treatment and chemotherapy as follows: abiraterone acetate plus prednisone (abiraterone)-docetaxel (ABI-DOCE), abiraterone-enzalutamide (ABI-ENZA), abiraterone–radium-223 (ABI-RAD), docetaxel-abiraterone (DOCE-ABI), docetaxel-cabazitaxel (DOCE-CABA), docetaxel-enzalutamide (DOCE-ENZA), and enzalutamide-docetaxel (ENZA-DOCE). Outcome measurements and statistical analysis: Baseline patient characteristics, quality of life, mCRPC treatments, and efficacy outcomes (progression and survival) were presented descriptively. Results and limitations: Data from 727 patients were eligible for the analysis (ABI-DOCE n = 178, ABI-ENZA n = 99, ABI-RAD n = 27, DOCE-ABI n = 191, DOCE-CABA n = 74, DOCE-ENZA n = 116, and ENZA-DOCE n = 42). Demographics and disease characteristics among patients between different sequences varied greatly. Most patients who started on abiraterone or enzalutamide stopped therapy because of disease progression. No randomisation to allow treatment/sequence comparisons limited this observational study. Conclusions: The real-world PCR data complement clinical trial data, reflecting more highly selected patient populations than seen in routine clinical practice. Baseline characteristics play a role in mCRPC first-line treatment selection, but other factors, such as treatment availability, have an impact. Efficacy observations are limited and should be interpreted with caution. Patient summary: Baseline characteristics appear to have a role in the first-line treatment selection of metastatic castration-resistant prostate cancer in the real-world setting. First-line abiraterone acetate plus prednisone seems to be the preferred treatment option for older patients and those with lower Gleason scores, first-line docetaxel for younger patients and those with more advanced disease, and first-line enzalutamide for patients with fewer metastases and more favourable performance status. The benefit to patients from these observations remains unknown

PD-L1 expression in tumor and inflammatory cells is associated with favorable tumor features and favorable prognosis in muscle-invasive urothelial carcinoma of the bladder not treated by immune checkpoint inhibitors

Abstract Background A high level of PD-L1 expression is the most relevant predictive parameter for response to immune checkpoint inhibitor (CPI) therapy in urinary bladder cancer. Existing data on the relationship between PD-L1 expression and the natural course of disease are controversial and sparse. Methods To expand our understanding of the relationship between PD-L1 expression and parameters of cancer aggressiveness, PD-L1 was analyzed on tissue microarrays containing 2710 urothelial bladder carcinomas including 512 patients with follow-up data who underwent radical cystectomy and follow-up therapies in the pre-immune checkpoint inhibitor therapy era. Results Tumor cell positivity in ≥10% of cells were seen in 513 (20%) and an immune cell positivity occurred in 872 (34%) of 2566 interpretable cancers. PD-L1 positivity in tumor cells increased from pTaG2 low grade (0.9% positive) to pTaG3 high grade (4.1%; p = 0.0255) and was even higher in muscle-invasive (pT2–4) carcinomas (29.3%; p < 0.0001). However, within pT2–4 carcinomas, PD-L1 positivity was linked to low pT stage (p = 0.0028), pN0 (p < 0.0001), L0 status (p = 0.0005), and a better prognosis within 512 patients with cystectomy who never received CPIs (p = 0.0073 for tumor cells and p = 0.0086 for inflammatory cells). PD-L1 staining in inflammatory cells was significantly linked to PD-L1 staining in tumor cells (p < 0.0001) and both were linked to a positive p53 immunostaining (p < 0.0001). Conclusion It cannot be fully excluded that the strong statistical link between PD-L1 status and favorable histological tumor features as well as better prognosis could influence the outcome of studies evaluating CPIs in muscle-invasive urothelial carcinoma

CEA (CEACAM5) expression is common in muscle‐invasive urothelial carcinoma of the bladder but unrelated to the disease course

Abstract Objectives Carcinoembryonic antigen (CEA) is a cell surface glycoprotein that represents a promising therapeutic target. Serum measurement of shedded CEA can be utilized for monitoring of cancer patients. Material and Methods To evaluate the potential clinical significance of CEA expression in urothelial bladder neoplasms, CEA was analysed by immunohistochemistry in more than 2500 urothelial bladder carcinomas in a tissue microarray format. Results CEA staining was largely absent in normal urothelial cells but was observed in 30.4% of urothelial bladder carcinomas including 406 (16.7%) with weak, 140 (5.8%) with moderate, and 192 (7.9%) with strong staining. CEA positivity occurred in 10.9% of 411 pTaG2 low‐grade, 32.0% of 178 pTaG2 high‐grade, and 43.0% of 93 pTaG3 tumours (p  0.25). Conclusion CEA increases markedly with grade progression in pTa tumours, and expression occurs in a significant fraction of pT2–4 urothelial bladder carcinomas. The high rate of CEA positivity in pT2–4 carcinomas offers the opportunity of using CEA serum measurement for monitoring the clinical course of these cancers. Moreover, CEA positive urothelial carcinomas are candidates for a treatment by targeted anti‐CEA drugs