Remote sensing data fusion approach for estimating forest degradation: a case study of boreal forests damaged by Polygraphus proximus DOI Creative Commons
Svetlana Illarionova, Polina Tregubova, Islomjon Shukhratov

и другие.

Frontiers in Environmental Science, Год журнала: 2024, Номер 12

Опубликована: Июль 31, 2024

In the context of global climate change and rising anthropogenic loads, outbreaks both endemic invasive pests, pathogens, diseases pose an increasing threat to health, resilience, productivity natural forests forest plantations worldwide. The effective management such threats depends on opportunity for early-stage action helping limit damage expand, which is difficult implement large territories. Recognition technologies based analysis Earth observation data are basis tools monitoring spread degradation processes, supporting pest population control, management, conservation strategies in general. this study, we present a machine learning-based approach recognizing damaged using open source remote sensing images Sentinel-2 supported with Google example bark beetle, Polygraphus proximus Blandford, polygraph. For algorithm development, first investigated annotated channels corresponding color perception—red, green, blue—available at Earth. Deep neural networks were applied two problem formulations: semantic segmentation detection. As result conducted experiments, developed model that quantitative assessment changes target objects high accuracy, achieving 84.56% F1-score, determining number trees estimating areas occupied by withered stands. obtained masks further integrated medium-resolution achieved 81.26% opened operational systems recognize region, making solution rapid cost-effective. Additionally, unique dataset has been collected polygraph region study.

Язык: Английский

Latest Trends in Modelling Forest Ecosystems: New Approaches or Just New Methods? DOI Creative Commons
Juan A. Blanco, Yueh‐Hsin Lo

Current Forestry Reports, Год журнала: 2023, Номер 9(4), С. 219 - 229

Опубликована: Июнь 15, 2023

Abstract Purpose of Review Forest models are becoming essential tools in forest research, management, and policymaking but currently under deep transformation. In this review the most recent literature (2018–2022), we aim to provide an updated general view main topics attracting efforts modelers, trends already place, some current future challenges that field will face. Recent Findings Four major on modelling efforts: data acquisition, productivity estimation, ecological pattern predictions, management related ecosystem services. Although may seem different, they all converging towards integrated approaches by pressure climate change as coalescent force, pushing research into mechanistic, cross-scale simulations functioning structure. Summary We conclude is experiencing exciting challenging time, due combination new methods easily acquire massive amounts data, techniques statistically process such refinements mechanistic incorporating higher levels complexity breaking traditional barriers spatial temporal scales. However, available also creating challenges. any case, increasingly acknowledged a community interdisciplinary effort. As such, ways deliver simplified versions or easy entry points should be encouraged integrate non-modelers stakeholders since its inception. This considered particularly academic modelers increasing mathematical models.

Язык: Английский

Процитировано

16

Predicting the potential distribution and forest impact of the invasive species Cydalima perspectalis in Europe DOI
Quim Canelles,

Emili Bassols,

Jordi Vayreda

и другие.

Ecology and Evolution, Год журнала: 2021, Номер 11(10), С. 5713 - 5727

Опубликована: Март 26, 2021

Abstract Invasive species have considerably increased in recent decades due to direct and indirect effects of ever‐increasing international trade rates new climate conditions derived from global change. We need better understand how the dynamics early invasions develop these result impacts on invaded ecosystems. Here we studied distribution severe defoliation processes box tree moth ( Cydalima perspectalis W.), a defoliator insect native Asia invasive Europe since 2007, through combination models based landscape composition information. The results showed that data areas was most effective methodology for appropriate modeling. not influenced by overall factors, but only presence its host plant, dispersal capacity, suitability. Such suitability described low precipitation seasonality minimum annual temperatures around 0°C, defining continentality effect throughout territory. emphasize studying separately because identified slightly involved limiting spread strongly constrained ecosystem impact terms before reaches equilibrium with environment. New studies habitat recovery after disturbance, ecological consequences such impact, community context change are required understanding this species.

Язык: Английский

Процитировано

24

Spatiotemporal outbreak dynamics of bark and wood-boring insects DOI
María Victoria Lantschner, Juan C. Corley

Current Opinion in Insect Science, Год журнала: 2022, Номер 55, С. 101003 - 101003

Опубликована: Дек. 31, 2022

Язык: Английский

Процитировано

17

Predicting the Global Potential Suitable Distribution of Fall Armyworm and Its Host Plants Based on Machine Learning Models DOI Creative Commons

Yanru Huang,

Yingying Dong, Wenjiang Huang

и другие.

Remote Sensing, Год журнала: 2024, Номер 16(12), С. 2060 - 2060

Опубликована: Июнь 7, 2024

The fall armyworm (Spodoptera frugiperda) (J. E. Smith) is a widespread, polyphagous, and highly destructive agricultural pest. Global climate change may facilitate its spread to new suitable areas, thereby increasing threats host plants. Consequently, predicting the potential distribution for plants under current future scenarios crucial assessing outbreak risks formulating control strategies. This study, based on remote sensing assimilation data plant protection survey data, utilized machine learning methods (RF, CatBoost, XGBoost, LightGBM) construct prediction models 120 Hyperparameter stacking ensemble method (SEL) were introduced optimize models. results showed that SEL demonstrated optimal performance in armyworm, with an AUC of 0.971 ± 0.012 TSS 0.824 0.047. Additionally, LightGBM 47 30 plants, respectively. Overlay analysis suggests overlap areas interaction links between will generally increase future, most significant rise RCP8.5 scenario, indicating threat further intensify due change. findings this study provide support planning implementing global intercontinental long-term pest management measures aimed at mitigating impact food production.

Язык: Английский

Процитировано

4

Remote sensing data fusion approach for estimating forest degradation: a case study of boreal forests damaged by Polygraphus proximus DOI Creative Commons
Svetlana Illarionova, Polina Tregubova, Islomjon Shukhratov

и другие.

Frontiers in Environmental Science, Год журнала: 2024, Номер 12

Опубликована: Июль 31, 2024

In the context of global climate change and rising anthropogenic loads, outbreaks both endemic invasive pests, pathogens, diseases pose an increasing threat to health, resilience, productivity natural forests forest plantations worldwide. The effective management such threats depends on opportunity for early-stage action helping limit damage expand, which is difficult implement large territories. Recognition technologies based analysis Earth observation data are basis tools monitoring spread degradation processes, supporting pest population control, management, conservation strategies in general. this study, we present a machine learning-based approach recognizing damaged using open source remote sensing images Sentinel-2 supported with Google example bark beetle, Polygraphus proximus Blandford, polygraph. For algorithm development, first investigated annotated channels corresponding color perception—red, green, blue—available at Earth. Deep neural networks were applied two problem formulations: semantic segmentation detection. As result conducted experiments, developed model that quantitative assessment changes target objects high accuracy, achieving 84.56% F1-score, determining number trees estimating areas occupied by withered stands. obtained masks further integrated medium-resolution achieved 81.26% opened operational systems recognize region, making solution rapid cost-effective. Additionally, unique dataset has been collected polygraph region study.

Язык: Английский

Процитировано

4