Assessing citizen science opportunities in forest monitoring using probabilistic topic modelling

Background： With mounting global environmental, social and economic pressures the resilience and stability of forests and thus the provisioning of vital ecosystem services is increasingly threatened. Intensified monitoring can help to detect ecological threats and changes earlier, but monitoring resources are limited. Participatory forest monitoring with the help of ＂citizen scientists＂ can provide additional resources for forest monitoring and at the same time help to communicate with stakeholders and the general public. Examples for citizen science projects in the forestry domain can be found but a solid, applicable larger framework to utilise public participation in the area of forest monitoring seems to be lacking. We propose that a better understanding of shared and related topics in citizen science and forest monitoring might be a first step towards such a framework. Methods： We conduct a systematic meta-analysis of 1015 publication abstracts addressing ＂forest monitoring＂ and ＂citizen science＂ in order to explore the combined topical landscape of these subjects. We employ ＇topic modelling an unsupervised probabilistic machine learning method, to identify latent shared topics in the analysed publications. Results： We find that large shared topics exist, but that these are primarily topics that would be expected in scientific publications in general. Common domain-specific topics are under-represented and indicate a topical separation of the two document sets on ＂forest monitoring＂ and ＂citizen science＂ and thus the represented domains. While topic modelling as a method proves to be a scalable and useful analytical tool, we propose that our approach could deliver even more useful data if a larger document set and full-text publications would be available for analysis. Conclusions： We propose that these results, together with the observation of non-shared but related topics, point at under-utilised opportunities for public participation in forest monitoring. Citizen science could be applied as a versatile tool in forest ecosystems monitoring, complementing traditional forest monitoring programmes, assisting early threat recognition and helping to connect forest management with the general public. We conclude that our presented approach should be pursued further as it may aid the understanding and setup of citizen science efforts in the forest monitoring domain.

Combining Geomatics and Conventional Methods for Monitoring Forest Conditions under Different Governance Arrangements

This study employed an innovative meth- odological framework that combines geomatics and conventional survey methods to monitor changes in forest conditions and examine their associations with local forest governance parameters in a mountain watershed covering 153.3 km2 in the middle moun- tains of Nepal. The study involved two spatial scales and analytical steps. First, geomatics techniques were used to map and detect changes in major land cover types in the watershed between 1976 and 2000 and to analyze relationships between forest cover changes and governance arrangements. This was followed by micro-level analysis of the relationships between the biological conditions of selected forests within the watershed and their governance arrangements, using conventional survey methods and analytical tools. The findings show that forest cover in the watershed in- creased by about 15 per cent during the period. The rate of increase in forest cover was highest in areas under a semi-government type of governance ar- rangement, while the community forests were gener- ally better in terms of current biological conditions compared to the semi-government forests. This in- consistency between the findings from the two analy- ses does not allow us to draw any firm conclusions regarding the role of property rights in determining forest condition, but it indicates that the outcomes of local forest management initiatives may be more de-pendent on local institutional arrangements regulat- ing forest use and maintenance of forest resources than on the type of property rights arrangements. The findings also provide evidence of the methodological suitability of the research approach adopted, which may be useful for addressing many other research questions related to forestry and natural resources management, particularly those involving multiple spatial scales.

Monitoring of Forests Indicates Decrease of Important Elements in Tree Nutrition of Main Tree Species across the Czech Republic and Slovakia over the Long Term

Authors analysed foliar nutrition data from the ICP Forests(International Co-operative Programme on the Assessment and Monitoring of Air Pollution on Forests)monitoring network in two neighbouring Central European countries:the CZ(Czech Republic)and SK(Slovakia).Authors evaluated altogether seven coniferous(six Norway spruce and one Scots pine)and six broadleaves(five European beech and one Sessile oak)in intensively monitored plots.The longest time series cover more than 20 years(1995-2017 in CZ;1995-2013 in SK).The data show a significant decrease of the concentration of major nutrients,mainly P and K.On roughly half of plots,the concentration of P is near or below the deficiency limit(1.2 g·kg-1),the concentration of K has dropped by 10%to 50%,especially in stands of broadleaves during the evaluated period.Over time P and K have shown significantly decreasing trends on one third of the evaluated coniferous plots and a similar situation has occurred on broadleaf plots.Both countries differ in Mg trends-there is a decrease of Mg concentration in needles in SK compared with Czech coniferous plots.On the other hand,in beech leaves there is a decrease of Mg in both countries,and in CZ the trend over time for Mg is significant.The observed changes in nutrition level with stable or slightly increasing N concentration and with a drop in phosphorus and base cations have led to nutrient imbalance,especially between N and P.

Monitoring Forest Recovery in Protected Forests of Northern Côte d’Ivoire Using Landsat Imagery and Intensity Change Analysis

In this paper, the initiatives of reforestation of the national forests of the North of the Côte d’Ivoire were examined using geomatics and the analysis of change of intensity by taking the case of the protected Forest of Badénou (PFB). A spatial analysis based on multi-spectral and multi-temporal Landsat imagery was carried out to assess land cover changes in the (PFB) over the past two decades and determine whether patterns of change in terms of the intensity of gains/losses of each of the land cover classes were active or dormant between the period before (2000-2013) and after (2013-2019) the reforestation initiative. Five main classes were identified: forest (dry deciduous and gallery forests), tree savannah, shrub/grassy savannah (including agricultural lands), bare lands (bare soils and degraded land areas), and water course. All classes were satisfactorily classified, with an excellent producer’s and user’s and overall accuracies and very good Kappa coefficients. The results showed that between 2000 and 2019, the forest cover in the PFB increased from 7778 ha to 5054 ha, a decrease was marked between 2000 and 2013 of approximately 60% compared to its size in 2000, while a slight increase between 2013 and 2019 (4645 ha to 5054 ha) i.e. around 9%) certainly due to the reforestation since 2016. As for the annual intensities of change for each class in both study periods, changes (gain or loss) in forest and tree savanna were relatively dormant after reforestation, while annual bare land gain was relatively active and marked, indicating that degradation of forests remains a threat to the sustainability of the PFB. Forest degradation has occurred mainly in the eastern parts of the PFB, while the central parts have regained more tree cover. These results can help identify conservation and restoration priorities and improve the overall management of the PFB.

Accuracy of tree mapping based on hand-held laser scanning comparing leaf-on and leaf-off conditions in mixed forests

The use of mobile laser scanning to survey forest ecosystems is a promising,scalable technology to describe forest 3D structures at high resolution.To confirm the con-sistency in the retrieval of forest structural parameters using hand-held laser scanning(HLS),before operationalizing the method,confirming the data is crucial.We analyzed the per-formance of tree-level mapping based on HLS under differ-ent phenology conditions on a mixed forest in western Spain comprising Pinus pinaster and two deciduous species,Alnus glutinosa and Quercus pyrenaica.The area was surveyed twice during the growing season(July 2022)and once in the deciduous season(February 2022)using several scan-ning paths.Ground reference data(418 trees,15 snags)was used to calibrate the HLS data and to assess the influence of phenology when converting 3D data into tree-level attrib-utes(DBH,height and volume).The HLS-based workflow was robust at isolating tree positions and recognizing stems despite changes in phenology.Ninety-six percent of all pairs matched below 65 cm.For DBH,phenology barely altered estimates.We observed a strong agreement when comparing HLS-based tree height distributions.The values exceeded 2 m when comparing height measurements,confirming height data should be carefully used as reference in remote sensing-based inventories,especially for deciduous species.Tree volume was more precise for pines(r=0.95,and rela-tive RMSE=21.3–23.8%)compared to deciduous species(r=0.91–0.96,and relative RMSE=27.3–30.5%).HLS data and the forest structural complexity tool performed remark-ably,especially in tree positioning considering mixed forests and mixed phenology conditions.

Development of Long-Range,Low-Powered and Smart IoT Device for Detecting Illegal Logging in Forests

Forests promote the conservation of biodiversity and also play a crucial role in safeguarding theenvironment against erosion,landslides,and climate change.However,illegal logging remains a significant threatworldwide,necessitating the development of automatic logging detection systems in forests.This paper proposesthe use of long-range,low-powered,and smart Internet of Things(IoT)nodes to enhance forest monitoringcapabilities.The research framework involves developing IoT devices for forest sound classification andtransmitting each node’s status to a gateway at the forest base station,which further sends the obtained datathrough cellular connectivity to a cloud server.The key issues addressed in this work include sensor and boardselection,Machine Learning(ML)model development for audio classification,TinyML implementation on amicrocontroller,choice of communication protocol,gateway selection,and power consumption optimization.Unlike the existing solutions,the developed node prototype uses an array of two microphone sensors forredundancy,and an ensemble network consisting of Long Short-Term Memory(LSTM)and ConvolutionalNeural Network(CNN)models for improved classification accuracy.The model outperforms LSTM and CNNmodels when used independently and also gave 88%accuracy after quantization.Notably,this solutiondemonstrates cost efficiency and high potential for scalability.

Empowering fall webworm surveillance with mobile phone-based community monitoring: a case study in northern China

Recent advances in information and communication technologies, such as mobile Internet and smart- phones, have created new paradigms for participatory environment monitoring. The ubiquitous mobile phones with capabilities such as a global positioning system, camera, and network access, offer opportunities to estab- lish distributed monitoring networks that can perform a wide range of measurements for a landscape. This study examined the potential of mobile phone-based community monitoring of fall webworm （Hyphantria cunea Drury）. We built a prototype of a participatory fall webworm monitoring System based on mobile devices that stream- lined data collection, transmission, and visualization. We also assessed the accuracy and reliability of the data collected by the local community. The system performance was evaluated at the Ziya commune of Tianjin municipality in northern China, where fall webworm infestation has occurred. The local community provided data with accuracy comparable to expert measurements （Willmott＇s index of agreement 〉0.85）. Measurements by the local community effectively complemented remote sensing images in both temporal and spatial resolution.

Testing visible ozone injury within a Light Exposed Sampling Site as a proxy for ozone risk assessment for European forests

Biologically meaningful and cost-effective indicators are needed for assessing and monitoring the impacts of tropospheric ozone(0_(3)) on vegetation and are required in Europe by the National Emission Ceilings Directive(2016).However,a clear understanding on the best suited indicators is missing.The MOTTLES(MOnitoring ozone injury for seTTing new critical LEvelS) project set up a new generation network for 0_(3) monitoring in forest plots in order to:1) estimate the stomatal 0_(3) fluxes(Phytotoxic Ozone Dose above a threshold Y of uptake,PODY);and 2) collect visible foliar 0_(3) injury,both within the forest plot(ITP) and along the Light Exposed Sampling Site(LESS) along the forest edge.Nine forest sites at high 0_(3) risk were selected across Italy over 2017-2019 and significant correlations(p <0.05) were found between the percentage of symptomatic plant species within the LESS,and POD1(PODY,with Y=1 nmol 0_(3) m^(-2) s^(-1)) calculated for mixed forest species(r=0.53)and with the occurrence and severity of visible foliar 0_(3) injury on the dominant species in the plots(r=0.65).A generic flux-based critical level for mixed forest species was derived within the LESS and it was recommended using11 mmol m^(-2) POD1 as the critical level for forest protection against 0_(3) injury,similar to the critical level obtained in the ITP(12 mmol m^(-2) POD1).It was concluded that the frequency of symptomatic plant species within a LESS is a suitable and effective plant-response indicator of phytotoxic 0_(3) levels in forest monitoring.LESS is a non-destructive,less complex and less time-consuming approach compared to the ITP for monitoring foliar 0_(3) injury in the long term.Assessing visible foliar 0_(3) injury in the ITP might only underestimate the 0_(3) risk assessment at individual sites.These results are biologically meaningful and useful to monitoring experts and environmental policy makers.

A multi-purpose National Forest Inventory in Bangladesh:design,operationalisation and key results

Background:National forest inventory and forest monitoring systems are more important than ever considering continued global degradation of trees and forests.These systems are especially important in a country like Bangladesh,which is characterised by a large population density,climate change vulnerability and dependence on natural resources.With the aim of supporting the Government’s actions towards sustainable forest management through reliable information,the Bangladesh Forest Inventory(BFI)was designed and implemented through three components:biophysical inventory,socio-economic survey and remote sensing-based land cover mapping.This article documents the approach undertaken by the Forest Department under the Ministry of Environment,Forests and Climate Change to establish the BFI as a multipurpose,efficient,accurate and replicable national forest assessment.The design,operationalization and some key results of the process are presented.Methods:The BFI takes advantage of the latest and most well-accepted technological and methodological approaches.Importantly,it was designed through a collaborative process which drew from the experience and knowledge of multiple national and international entities.Overall,1781 field plots were visited,6400 households were surveyed,and a national land cover map for the year 2015 was produced.Innovative technological enhancements include a semi-automated segmentation approach for developing the wall-to-wall land cover map,an object-based national land characterisation system,consistent estimates between sample-based and mapped land cover areas,use of mobile apps for tree species identification and data collection,and use of differential global positioning system for referencing plot centres.Results:Seven criteria,and multiple associated indicators,were developed for monitoring progress towards sustainable forest management goals,informing management decisions,and national and international reporting needs.A wide range of biophysical and socioeconomic data were collected,and in some cases integrated,for estimating the indicators.Conclusions:The BFI is a new information source tool for helping guide Bangladesh towards a sustainable future.Reliable information on the status of tree and forest resources,as well as land use,empowers evidence-based decision making across multiple stakeholders and at different levels for protecting natural resources.The integrated socioeconomic data collected provides information about the interactions between people and their tree and forest resources,and the valuation of ecosystem services.The BFI is designed to be a permanent assessment of these resources,and future data collection will enable monitoring of trends against the current baseline.However,additional institutional support as well as continuation of collaboration among national partners is crucial for sustaining the BFI process in future.

Assessment of forest dieback on the Moroccan Central Plateau using spectral vegetation indices

Cork oak forests in Morocco are rich in resources and services thanks to their great biological diversity,playing an important ecological and socioeconomic role.Considerable degradation of the forests has been accentuated in recent years by signifi cant human pressure and eff ects of climate change;hence,the health of the stands needs to be monitored.In this study,the Google Engine Earth platform was leveraged to extract the normalized diff erence vegetation index(NDVI)and soil-adjusted vegetation index,from Landsat 8 OLI/TIRS satellite images between 2015 and 2017 to assess the health of the Sibara Forest in Morocco.Our results highlight the importance of interannual variations in NDVI in forest monitoring;the variations had a signifi cantly high relationship(p<0.001)with dieback severity.NDVI was positively and negatively correlated with mean annual precipitation and mean annual temperature with respective coeffi cients of 0.49 and−0.67,highlighting its ability to predict phenotypic changes in forest species.Monthly interannual variation in NDVI between 2016 and 2017 seemed to confi rm fi eld observations of cork oak dieback in 2018,with the largest decreases in NDVI(up to−38%)in December in the most-aff ected plots.Analysis of the infl uence of ecological factors on dieback highlighted the role of substrate as a driver of dieback,with the most severely aff ected plots characterized by granite-granodiorite substrates.

The Spatial-Temporal Heterogeneity of Understory Light Availability in a Temperate Forest of North China

The spatial-temporal variation of understory light availability has important influences on species diversity and community assembly.However,the distribution characteristics and influencing factors of understory light availability have not been fully elucidated,especially in temperate deciduous,broad-leaved forests.In this study,the understory light availability was monitored monthly(May–October)in a temperate deciduous,broad-leaved forest in Henan Province,China.Differences in the light availability among different months and habitat types were statistically analyzed using Kruskal–Wallis method,respectively.Partial least squares path modeling(PLS-PM)was used to explore the direct and/or indirect effects of stand structure,dominant species and topographic factors on the light environment.Results showed that there were differences in light environments among the four habitat types and during the studied six months.The PLS-PM results showed that the stand structure and the dominant species were negatively correlated with the light environment,and the path coefficient values were−0.089(P=0.042)and−0.130(P=0.004),respectively.Our result indicated that the understory light availability exhibit a distinct spatial and temporal heterogeneity in temperate deciduous,broad-leaved forest of north China.The characteristics of woody plant community,especially the abundance of one of the dominant plant species,were the important factors affecting the understory light availability.

Monitoring Hotspots Using Thermal Sensors on MODIS Aqua/Terra Satellite System: A Case Study of National Park Areas in Northern Thailand

This research presents the remote sensing data on hotspots in four national parks located in Chiang Mai province, Thailand: Sri Lanna National Park, Huai Nam Dang National Park, Doi Pahom Pok National Park, and Doi Inthanon National Park. To mitigate the devastating impacts of these wildfires, effective monitoring and management strategies are necessary. Remote sensing technology provides a promising approach for mapping burnt areas and understanding fire regimes at a regional scale. The primary focus of this research is to employ the MODIS Aqua/Terra satellite system for obtaining historical remote sensing data on hotspots. The advantages of remote sensing include accurate identification and mapping of burnt areas, regular monitoring, rapid data acquisition, and historical data analysis. The MODIS sensor, specifically designed for fire monitoring, offers enhanced fire detection and diagnosis, multiple channels for qualitative and quantitative analysis, and precision positioning capabilities. The research results presented in the analysis contribute to the understanding of fire incidents and hotspot occurrences within the four national parks studied. This paper suggests the optimization of early detection of forest and land fires through the utilization of Artificial Intelligence (AI), presenting it as a recommendation for future endeavors. The research emphasizes the significance of implementing efficient policies and management strategies to effectively tackle the challenges associated with fires in these ecologically significant areas.

Exploring tree diversity and stand structure of savanna woodlands in southeastern Sudan

Savanna woodlands in Sudan host great biodiversity, provide a plethora of ecosystem goods and services to local communities, and sustain numerous ecological functions. Although the importance of the Acacia trees in these areas is well known, up-to-date information about these woodlands' diversity is limited and changes in their woody vegetation composition, density, diversity and relative frequency are not monitored over time. This study explored tree diversity and stand stage structure in Nuara Reserved Forest, a typical savanna woodland ecosystem in southeastern Sudan. A total of 638 circular sample plots(1000 m^2 for each) were established using a systematic sampling grid method. The distance between plots was 200 m. In each plot, all living trees with diameter at breast height(DBH) ≥5.00 cm were identified and counted, and their DBH values were recorded. From these data, tree composition, diversity, density and stage structure were assessed. There were 12,259 individual trees representing four species(Acacia seyal, Balanites aegyptiaca, Acacia Senegal and Acacia mellifera) that belong to two families. The dominant species was Acacia seyal. Average tree density was 191 trees/hm^2 and the Shannon-Weiner index for trees diversity was 0.204. Overall, young trees comprised 86.30% of the forest. The state of tree richness and density in the study area was low compared to other similar environments in the region and around the world. We recommended adoption of a proper management system that includes monitoring of woody vegetation diversity in this forest, and management actions to enhance tree diversity and sustain ecosystem services to local communities. In addition to care for the dominant Acacia seyal stands, more attention and conservation should be devoted to reestablishing Acacia senegal and Acacia mellifera trees because of their high ecological and economic values for local communities.

Bridging experimental and monitoring research for visible foliar injury as bio-indicator of ozone impacts on forests

Tropospheric ozone(O_(3))is a phytotoxic air pollutant and the O_(3)-induced visible foliar injury(O_(3)VFI)is a biomarker.A recently developed Free-air O_(3)eXposure(FO_(3)X)is a promising facility to verify field-observed“O_(3)-like”VFIs and to establish a flux-based threshold for the O_(3)VFI onset.The present study compared O_(3)-like VFI registered in the southern European forest sites with actual O_(3)VFI observed in a FO_(3)X experiment.The O_(3)-like VFIs were evaluated by eye in forests and thus it was subjective.According to the imaging analysis,we firstly demonstrated that major parts of the colors were similar in the field and the FO_(3)X.The color pallets for O_(3)VFI was species-specific and considered a advanced tool for the O_(3)VFI diagnosis.In addition,we calculated a flux-based threshold for the O_(3)VFI onset at the FO_(3)X based on a Phytotoxic Ozone Dose(POD_(1)),which ranged from 4.9 to 18.1 mmol m^(-2)POD1.This FO_(3)X-derived threshold partly explained but did not necessarily match with the observation for several tree species in actual forests.The multivariate analysis showed that O_(3)VFI was decreased by the presence of various species and suggested the importance of continuous monitoring activities in the field for the further analysis.

Determining the Drying Out of Coniferous Trees Using Airborne and Satellite Data

In recent decades, the problem of drying out of conifers has become a subject of significant importance due to the widespread mortality of trees caused by stem pest’s damage. Early detection of areas affected by insect outbreaks is of great relevance for preventing the further spread of pests. Forests of Belarus are largely affected by conifers dieback caused by the bark beetle. The aim of the study was to identify drying out conifers using a TripleSat satellite multispectral image of a woodland area in Belarus based on preliminary airborne measurements. Spectrometers operating in a spectral range of 400 - 900 nm were used in airborne measurements, resulting in distinguishing various drying out stages with an accuracy of 27% - 74% for aerial data. In this study, a supervised classification of the TripleSat image based on the method of linear discriminant analysis (LDA) was performed. The input data for LDA algorithm is a set of remote sensing vegetation indices. Results of the study demonstrate that about 90% of the test site is at the green-attack stage that is confirmed by ground surveys of this area.

The global Landsat imagery database for the FAO FRA remote sensing survey

To collect and provide periodically updated information on global forest resources,their management and use,the United Nations Food and Agriculture Organization(FAO)has been coordinating global forest resources assessments(FRA)every 5
10 years since 1946.To complement the FRA national-based statistics and to provide an independent assessment of forest cover and change,a global remote sensing survey(RSS)has been organized as part of FAO FRA 2010.In support of the FAO RSS,an image data set appropriate for global analysis of forest extent and change has been produced.Landsat data from the Global Land Survey 1990
2005 were systematically sampled at each longitude and latitude intersection for all points on land.To provide a consistent data source,an operational algorithm for Landsat data pre-processing,normalization,and cloud detection was created and implemented.In this paper,we present an overview of the data processing,characteristics,and validation of the FRA RSS Landsat dataset.The FRA RSS Landsat dataset was evaluated to assess overall quality and quantify potential limitations.