Natural Forest Areas Research Articles

Interpretação ambiental nos roteiros ecoturísticos da Floresta Nacional de Carajás – PA, Brasil

The creation and planning of natural areas protected contribute to the conservation and protection of natural diversity, in addition to reducing deforestation. These areas can be essential elements in the effectiveness of conservation, allied to the involvement of the population. However, when the subject is ecotourism or sustainable tourism in protected areas, it is important to highlight that the dimensions of sustainability will be influenced by tourism activities, due to the impacts it generates. Thus, it is important to internalize environmental education and environmental interpretation as means to promote awareness and effective involvement. Considering this context, the objective of the research carried out was to propose interpretative itineraries for visiting the National Forest area. The methodology for this work was to use the Brazilian version of the Recreation Opportunity Spectrum method to inventory existing natural attractions with ecotourism potential, located in the Amazon Forest biome. The results made it possible to suggest visiting itineraries that consider different public profiles, as well as possible themes that can be used in the environmental interpretation of each attraction and its potential for increasing public use. Furthermore, the results offer subsidies for the development of a pedagogical project of environmental education, in order to provide a better experience in the visitation and the reflection of visitors on contemporary issues affecting the Carajás National Forest.

Determination of model maps for the potential distribution of Anatolian black pine (Pinus nigra Arnold.) in natural forest areas in the Central Black Sea region

Özdemir ŞENTÜRK 1*, Serkan GÜLSOY 2, Mehmet Güvenç NEGİZ 3, Fatih KARAKAYA 2 ORCID: https://orcid.org/0000-0003-2513-6070; https://orcid.org/0000-0003-2011-8324; https://orcid.org/0000-0002-6338-3307; https://orcid.org/0000-0002-6534-6382 1 Gölhisar Vocational School, Departmant of Forestry, Burdur Mehmet Akif Ersoy University, Gölhisar, Burdur, Turkey 2 Faculty of Forestry, Department of Forest Engineering, Isparta University of Applied Sciences, Isparta, Turkey 3 Sütçüler Prof. Dr. Hasan GÜRBÜZ Vocational School, Department of Forest Engineering, Isparta University of Applied Sciences, Sütçüler, Isparta, Turkey *Corresponding author: e-mail: osenturk@mehmetakif.edu.tr Abstract The purpose of this study was to determine potential distribution modeling and mapping of Anatolian black pine in the Vezirköprü district. Presence / absence data of the species was collected from 586 sample areas. Environmental variables (elevation, slope, bedrock, radiation index etc.) were obtained from the digital maps. In addition, climatic variables were downloaded from WorldClim database. Generalized Additive Model and Classification and Regression Tree were used for potential distribution modeling of the species. The validation value of Generalized Additive Model was 0.84 while the cross-validation test value was found to be 0.82. Also, the ROC values of the tree model were found to be 0.804 for the training data set and 0.750 for the testing data set. According to the Classification and Regression Tree method, the locations above 650 m and without meta-sandstone are suitable for the potential distribution of the species. Under the condition that there is meta-sandstone, the areas where the temperature is between 7.6-11.0 °C and the slope degree is more than 23% coincide with the potential distribution of the species. Also, Generalized Additive Model showed that places where gabbro, ophiolitic melange, serpentine, and mixed material were seen as main bedrock type, sloping sites where average elevation was from 600 to 1150 m and temperature is between approximately 8.5-11.3 °C were the most suitable conditions for the potential distribution of the species in the district. In both models, it was determined that especially rock formations, climatic variable, and altitude are effective in the potential distribution of the species. On the other hand, although there are some differences in the variables in the models, the potential distribution maps formed by these variables overlapped quite. As a result, the information obtained in the study is important for the forestry practices such as afforestation, regeneration and the monitoring the species under future climate change conditions. Keywords: generalized additive model; classification and regression tree; species distribution model; Vezirköprü

Eucalyptus Species Discrimination Using Hyperspectral Sensor Data and Machine Learning

The identification of tree species is very useful for the management and monitoring of forest resources. When paired with machine learning (ML) algorithms, species identification based on spectral bands from a hyperspectral sensor can contribute to developing technologies that enable accurate forest inventories to be completed efficiently, reducing labor and time. This is the first study to evaluate the effectiveness of classification of five eucalyptus species (E. camaldulensis, Corymbia citriodora, E. saligna, E. grandis, and E. urophyla) using hyperspectral images and machine learning. Spectral readings were taken from 200 leaves of each species and divided into three dataset sizes: one set containing 50 samples per species, a second with 100 samples per species, and a third set with 200 samples per species. The ML algorithms tested were multilayer perceptron artificial neural network (ANN), decision trees (J48 and REPTree algorithms), and random forest (RF). As a control, a conventional approach by logistic regression (LR) was used. Eucalyptus species were classified by ML algorithms using a randomized stratified cross-validation with 10 folds. After obtaining the percentage of correct classification (CC) and F-measure accuracy metrics, the means were grouped by the Scott–Knott test at 5% probability. Our findings revealed the existence of distinct spectral curves between the species, with the differences being more marked from the 700 nm range onwards. The most accurate ML algorithm for identifying eucalyptus species was ANN. There was no statistical difference for CC between the three dataset sizes. Therefore, it was determined that 50 leaves would be sufficient to accurately differentiate the eucalyptus species evaluated. Our study represents an important scientific advance for forest inventories and breeding programs with applications in both forest plantations and native forest areas as it proposes a fast, accurate, and large-scale species-level classification approach.

Driving factors of tree biomass and soil carbon pool in xerophytic forests of northeastern Argentina

BackgroundThe conversion of forests into agricultural lands can be a threat because the forests carbon stored could be a source of emissions. The capacity to improve the predictions on the consequences of land use change depends on the identification of factors that influence carbon pools. We investigated the key driving factors of tree biomass and soil carbon pools in xerophytic forests in northeastern Argentina. Based on analyses of forest structure variables and abiotic factors (topography and soil properties) from 18 mature forests, we evaluated carbon pools using uni- and multivariate (redundancy analysis) methods.ResultsThe total carbon pool was estimated at 102.4 ± 24.0 Mg ha−1. Soil organic carbon storage is the single largest carbon pool relative to tree biomass, representing 73.1% of total carbon. Tree canopy cover and basal area were positively correlated with biomass carbon pool (r = 0.77 and r = 0.73, p < 0.001, respectively), proving to be significant drivers of carbon storage in this compartment. Slope, soil clay content and cation-exchange capacity had a better explanation for the variability in soil carbon pools, and all showed significant positive correlations with soil carbon pools (r = 0.64, 0.60 and 0.50; p < 0.05, respectively). The vertisols showed a 27.8% higher soil carbon stock than alfisols.ConclusionsThe relevance of our study stems from a dearth of information on carbon pools and their drivers in xerophytic forests, and in particular, the importance of this ecosystems’ type for Argentina, because they cover 81.9% of native forest area. Basal area and tree canopy cover exert a strong effect on the carbon pool in tree biomass but not in the soil. The results suggests that there is a potentially major SOC accumulation in forests located in slightly sloping areas and soils with higher topsoil clay content, such as vertisols. This could provide an important reference for implementing forestry carbon sink projects.

The Gender Aspects of Agroforestry Practices in Maytemeko Watershed, Northwestern Ethiopia

This study was conducted to assess the gender aspect of agroforestry practices (AFPs) in terms of participation and benefit in northwest Ethiopia. An explanatory sequential research design of mixed method was employed to obtain and analyze the data required for the study. Household questionnaire survey which was collected from 138 randomly selected households, ethnographic observation and interview were used to collect data. The research result showed that though most women are implementing AFPs compared to their male counterparts, the number of trees and shrubs on farm plots are lower for women. At household level, women are taking highest responsibility to manage AFPs. It was also found that 40.3% (166.5 tons/year) of energy for cooking and heating is obtained from trees and shrubs grown in AFPs followed by natural forest wood sources (32.2% or 134 tons/year). The majority of the respondents (56%) confirmed that women and girls are responsible for fuel wood collection from the natural forest areas. In contrast, for those households who obtained the fuel wood from AFPs, men are most responsible to prepare the fuel wood. An average time which was needed to collect a bundle of fuel wood from natural forest area was four times more than the time needed to collecting the same amount of fuel wood from AFPs. This indicated that AFP is playing a crucial role in reducing the burden of women and girls by reducing the time and labor spent for fuel collection. Generally, implementing AFP is not only used to save the natural forest cover, but it also has an implication in gender balance for fuel wood collection. Thus, stressing the multiple benefits of AFP, agricultural extension workers should encourage farmers to plant trees on their farm lands by recognzing the gender aspects as well.

Harvesting Bertholletia excelsa Bonpl. in a western Amazon rural community: local ecological knowledge and meaning to “nut-crackers”

IntroductionThe collection of Bertholletia excelsa Bonpl. (castanha-da-Amazônia; Brazil nuts) seeds make up part of the everyday activities of the traditional populations that have inhabited all of the Amazon basin since remote times. Nonetheless, knowledge about these harvesting activities in native forest areas has not been well documented. The present study was designed to better understand the significance of this harvesting activity as well as the traditional ecological knowledge of the harvesters.MethodsUtilizamos entrevistas semiestruturadas para a coleta de dados com extrativistas de castanha, moradores de Caroebe, Roraima (n = 18) durante o período de março de 2021 a março de 2022. The data analysis was based on the frequency of responses to socio-economic questions and their knowledge about that plant species as well as why those interviewees chose that line of work. We also adopted the Spearman and Mann–Whitney non-parametric tests to correlate variables identified in the study, and selected sections of their depositions to highlight the traditional knowledge of the interviewees and their experiences as harvesters.ResultsConstatamos que as razões para a escolha do trabalho com o extrativismo para todos os entrevistados é a necessidade de renda complementar, tradição familiar (55%), the sense of well-being provided by contact with the natural environment (25%), and a favorable disposition toward that type of work (11%). Harvesting involves collective work, and many of the interviewees had engaged in those efforts to help their families since their childhood or adolescence. The older harvesters cited more animal species that consumed the Brazil nuts (ρ = 0.60; p = 0.009) and perceived more and greater changes in the environment that were prejudicial to the Brazil nut trees (U = 9.50; p = 0.022). The interviewees who reported lower incomes cited more significant cultural changes and more suggestions concerning conservation activities. According to their statements, deforestation, and the burning and illegal cutting of native trees, including Brazil nut trees, have contributed to environmental change in the region and raised significant concerns about the future of harvesting activities.ConclusionThe activities of the “nut-crackers” represent to them more than just a simple source of income, as harvesting provides them with a connection to nature that promotes their well-being and cultural heritage. The nut harvesters have gained specific knowledge concerning both environmental and cultural changes. Those changes have mainly come about through the expansion of agricultural activities and the felling of native forests—which are the main threats to the future of Brazil nut extraction. Attributing value to the folk knowledge of those harvesters would strengthen the local economy, promote forest conservation, and help to better understand the impacts of anthropic activities on the forest and the harvesting of natural products.

FOREST FEATURE LIDAR SLAM (F2-LSLAM) AND INTEGRATED SCAN SIMULTANEOUS TRAJECTORY ENHANCEMENT AND MAPPING (IS2-TEAM) FOR ACCURATE FOREST INVENTORY USING BACKPACK SYSTEMS

Abstract. Under-canopy mapping is desired to derive critical forest biometrics, such as diameter at breast height (DBH), merchantable height, and debris volume. The main challenge of such under-canopy mapping is the intermittent access to the global navigation satellite system (GNSS) signal, which is crucial to deriving accurately georeferenced mapping products. In this study, we propose two frameworks – Forest Feature LiDAR Simultaneous Localization and Mapping (F2-LSLAM) and Integrated Scan Simultaneous Trajectory Enhancement and mapping (IS2-TEAM) – for 3D LiDAR unit mounted on backpack systems to achieve accurate forest inventory. In the F2-LSLAM strategy, ground/tree trunk features are extracted from individual LiDAR scans. On the other hand, when trajectory information provided by navigation sensors is available, these semantic features are derived from LiDAR points within several scans (i.e., integrated scan) for the IS2-TEAM strategy. Then, local/global least squares adjustment (LSA) using derived features is performed to register LiDAR scans to a common reference frame for both strategies. To evaluate the performance of the proposed strategies, three in-house developed backpack systems with varying specifications were used to collect data in complicated forest environments. Through the comparison with point clouds acquired by a commercial backpack LiDAR system, the proposed frameworks are capable of generating point clouds with satisfactory intra-dataset alignment quality (in the range of 2–4 cm) for all backpack systems in natural forest areas with relatively flat terrain. However, for more challenging areas with dense undergrowth vegetation and/or large height differences, F2-LSLAM framework cannot extract sufficient features, while IS2-TEAM still exhibits good performance.

Spatiotemporal changes of forest vegetation after the implementation of a natural forest protection project and underlying driving factors: Case study of a typical natural secondary forest area in the Loess Plateau

The Natural Forest Protection Project (NFPP) in China is the first large-scale ecological restoration project aimed at protecting natural forest resources in the world. However, since its implementation in 1998, there was a lack of accurate quantitative evaluation of the ecological governance and restoration effects. This study investigated the core forest area of Ziwuling on the Loess Plateau (LP). Using the Google Earth Engine (GEE) and the Landsat remote sensing dataset, a multidimensional classification feature set comprising spectrum + vegetation index + texture + terrain was constructed by extracting multitemporal remote sensing information. With the help of land use and vegetation type data, a sample database was established, after which the random forest algorithm was used to realize the automatic classification of the five periods of the study area in 2000, 2005, 2010, 2015 and 2020. Combined with geostatistical methods such as Theil-Sen (Sen) trend analysis, Mann-Kendall (MK) trend test and geographic detectors, we realized the trend analysis of the driving factors of vegetation growth and the contribution analysis of the spatial differentiation of different vegetation types. The results showed that: (1) From 2000 to 2020, the vegetation area increased by 141.92 km2. In terms of structural composition, the vegetation was dominated by hardwood forest, followed by sagebrush, and low coverage of coniferous forest. (2) Over time, the expansion of vegetation showed a positive slowing trend, and the growth rate in 2000–2005 was significantly higher than in 2005–2020. (3) The main driving force affecting vegetation restoration is precipitation, and the temperature plays a regulating role. (4) The main driving factors affecting the spatial differentiation of vegetation were annual maximum temperature, annual average temperature, and aspect. These findings not only help us understand the intuitive contribution of the NFPP to the vegetation restoration and ecological management of the LP, but also provide an important reference for future studies using remote sensing technology in ecological restoration monitoring.

Towards the vision of going green in South Asian region: The role of technological innovations, renewable energy and natural resources in ecological footprint during globalization mode

In order to achieve the objectives of 27th Paris Climate Conference (COP-27), this study aims to inspect the multifaceted interaction between natural resources, technological innovation, forest area, globalization, renewable energy, and ecological footprint of six South Asian countries from 1990 to 2020 of diminishing carbon emissions and encourage ecological sustainability. The long-term experiential estimations estimated from the battery of second-generation methods, which tackled other econometric estimation problems such as heterogeneity and cross-sectional dependency. The empirical outcomes discovered that natural resources and globalization process in South Asian region significantly increase the level of ecological footprint in the long-run. Conversely, technological innovations, forest area, and renewable energy upsurge environmental sustainability by reducing ecological footprint in the and long-run. Moreover, the interaction of natural resources with technological innovation, forest area, and renewable energy also adds in curtailing the level of ecological footprint and aid in achieving Sustainable Development Goals (SDGs) 13. Based on the estimated findings, substantial policy recommendations are suggested like improving the extraction of natural resources, promoting energy efficiency, investment in energy technologies, and increasing the deployment of renewable energy sources to increase technological invention and achieve the goal of a net-zero-emissions.

Ecological value of wood energy plantations in the support of some animal groups

Today, some environmental problems have reached such severe proportions that it is no longer enough to recognise them, but environmentally friendly solutions must be used to reduce them. The reduction in the area of natural forests of native species is causing problems in several ways. This research aimed to highlight how environmental, conservation and economic interests can be reconciled. In addition to natural forests, wood energy plantations are becoming increasingly important. Energy import dependency is a problem for most countries, for which wood energy plantations can partly offer an alternative. Native forests can be protected, and their area increased where possible. Meanwhile, energy plantations can be established in areas with low agricultural productivity. In this experiment, I studied a plantation of Pedunculate Oak (Quercus robur), a Black Locust (Robinia pseudoacacia) and a Paulownia (Paulownia Shan Tong). I selected burrowing birds and ground-dwelling arthropods as indicator groups. I did this by establishing a nesting colony and soil trapping. I wanted to demonstrate that, in addition to natural forests, wood energy plantations have a role not only in economic terms but also in maintaining certain animal groups. Soil trapping tests were carried out in all three tree plantations. The obtained results showed that in the Paulownia plantation, the occupancy rate of nest boxes was almost 100%, while in the Black Locust plantation it was around 30%. Among the species that occupied the nesting sites, the Common Starling (Sturnus vulgaris) and the Eurasian Tree Sparrow (Passer montanus) were more abundant, while Great Tit (Parus major) was present in the Black Locust plantation. These are opportunistic species for which nesting opportunity is the most important factor, since their feeding area (in the case of the Common Starling and the Eurasian Tree Sparrow) is not typical of the nesting area. The soil trap investigations show that there are no significant differences in the composition of the arthropod group (beetles, spiders) in the study areas.

Analisis Kebijakan Pemerintah Dalam Perlindungan Orangutan Di Provinsi Kalimantan Timur

The protection and management of conservation, biodiversity and ecosystems in Indonesia is essential, including the protection of endangered species. One of the endangered animals is the orangutan on the island of Borneo. In addition to the crushed, the orangutan population has also continued to decline due to poaching that has been rife over the past few decades. The area of natural forests from Indonesia is currently shrinking rapidly. So now animal life is increasingly threatened due to the rapid development of humans and increasingly sophisticated human civilization. The purpose of writing this article is to analyze the efforts made by the government in implementing policies in the protection of Bornean Orangutans. This research uses qualitative methods with a literature review approach. The results showed that the implementation of government policies in an effort to protect orangutans in Kalimantan is by conserving orangutans. However, in reality, conservation efforts often collide with various interests. Inhibiting policy implementation are the expansion of industrial estates and the conversion of forested areas that squeeze vast areas of orangutan habitat.

Effects of Land Use on Soil Physical-Hydric Attributes in Two Watersheds in the Southern Amazon, Brazil

Changes in land use can cause degradation of soil physical quality with negative effects on the environment and agricultural production. The effects of different land uses on soil physical-hydric attributes were studied in the Renato River and Caiabi River watersheds in the southern Brazilian Amazon. Three conditions of land use were evaluated: native forest, crops, and pasture in the headwater, middle, and mouth of each watershed. Particle size, particle density, bulk density, total porosity, macroporosity, microporosity, water contents at field capacity and permanent wilting point, and available water capacity in soil were evaluated in three soil layers down to 0.4 m. Data collected were subjected to the Kruskal–Wallis nonparametric test and Pearson’s correlations. Multivariate analyses were also performed using the principal component method. In the Renato watershed, in comparison with native forest, conventional management of pasture and crops caused soil physical degradation, increasing soil density in the surface layer and reducing macroporosity and total porosity. In the Caiabi watershed, converting native forest areas into pasture and crops altered water quality, influencing the water dynamics in the soil, by reducing soil water conductivity. Soil attributes varied by watershed, with texture variations between the headwater and mouth, indicating that changes in soil properties result from both management and the granulometric composition of the soil in different regions of the same watershed. Adoption of crop and pasture conservation practices can improve soil physical attributes in regions bordering agricultural areas in the southern Amazon.

Spatio-Temporal Dynamics and Physico-Hydrological Trends in Rainfall, Runoff and Land Use in Paraíba Watershed

The detection and monitoring of changes in land use and land cover play a crucial role in understanding land degradation and are fundamental to preserving agroecosystems. Their association with hydrological information allows essential responses to changes in hydrological patterns to be identified, contributing to water security in watersheds. Therefore, this study aimed to assess spatio-temporal dynamics and physico-hydrological trends in rainfall, runoff and land use in the Paraíba watershed. The study was conducted in the Paraíba watershed, using land use data and information from pluviometric and fluviometric stations with temporal series of more than 30 years. The Mann-Kendall statistical test was adopted to verify trends. Results indicate annual reduction trends for both native forest area and water bodies in the Paraíba watershed. On the other hand, the area designated for agriculture showed a significant increase. The correlation analysis between water bodies and forests (R² = 0.63) highlights a strong association between the decrease in forest area and the reduction in water availability, influencing the decrease in annual flow. These results serve as a warning to expand water resource management for the region, aiming to preserve and to enhance sustainable use. Therefore, the implementation of conservation measures, monitoring procedures, and adequate management is required to face the challenges imposed by climate change and land use and occupation, ensuring the water availability for the future.

Effects of protected areas on soil nematode communities in forests of the North of Portugal

AbstractNature conservation policy is mainly concerned with aboveground terrestrial species and soil biodiversity has been largely ignored, resulting in a lack of information about the conservation status of most soil organisms and about the effects that nature conservation policies have on soil systems. Forests in Northern Portugal are characterized by a remarkable diversity of ecosystems and provide habitat for an enormous diversity of living organisms. This study aims to investigate whether and to what extent protected areas and forest typology (native vs. exotic) affect soil nematode biodiversity and functions in forest ecosystems. We studied soil nematode communities, which have been widely used for their bioindicator value, to: (i) assess differences in soil biodiversity and functions between protected and non-protected areas, and between native and exotic forest types; and (ii) infer how protected areas deal with pressures and drivers of soil biodiversity and functions. We showed that current work done by nature conservation in Northern Portugal is producing some significant effects on the soil system, showing a larger Structure and Omnivore footprints and greater abundance of fungivorous and omnivorous nematodes in protected areas. Furthermore, native forest areas are better suited to ensure soil biodiversity and ecological functioning and should have a greater importance in nature conservation measures. Soil organic carbon, apparent density, soil moisture, and deciduous forest cover mainly influenced soil functional biodiversity with higher nematode trophic groups being positively associated with soil organic carbon and moisture and negatively associated with apparent density. Finally, conservation efforts targeted at the protection of native forests need to better consider effects on soil biodiversity and function, to provide an integrated protection of both aboveground and belowground components.

Spatio-Temporal Variation in Soil Salinity and Its Influencing Factors in Desert Natural Protected Forest Areas

Soil salinity is a crucial parameter affecting soil health. Excessive surface salt accumulation degrades soil structure, inhibits vegetation growth, and diminishes plant diversity. Such increases in salinity can accelerate desertification, leading to soil resource loss, hampering agricultural progress, and compromising ecological security. However, the vastness of arid regions and data acquisition challenges often hinder efficient SSC monitoring and modeling. In this study, we leveraged remote sensing data coupled with machine learning techniques to investigate the spatio-temporal dynamics of SSC in a representative desert natural forest area, the Alxa National Public Welfare Forest. Utilizing the geodetector model, we also delved into the factors influencing SSC. Our results underscored the effectiveness of the Convolutional Neural Networks (CNN) model in predicting SSC, achieving an accuracy of 0.745. Based on this model, we mapped the spatial distribution of SSC, revealing hydrothermal conditions as pivotal determinants of salt accumulation. From 2016 to 2021, soils impacted by salinity in the research area exhibited a rising trend, attributed to the prevailing dry climate and low precipitation. Such intensified salinity accumulation poses threats to the healthy growth of protective forest vegetation. This study can provide a theoretical reference for salinization management and ecological protection in desert natural forest areas.

Research on Compensation System for Ecological Environment Damage—Taking Ganzi Prefecture of Sichuan Province as an Example

The construction of ecological civilization is a process of sustainable development. Environmental protection extends from individual interests to social public interests, from general tort compensation to environmental public interest litigation and ecological environmental damage compensation, which effectively improves the ecological environment. As the most important natural forest distribution area in Sichuan Province, Ganzi Prefecture is an important part of the ecological protection barrier and “China Water tower” in the upper reaches of the Yangtze River and the Yellow River. It is rich in forest, grassland and wetland resources and has a good ecological environment. This paper mainly makes an empirical study of the ecological environment damage compensation system in Ganzi Prefecture, and puts forward some suggestions for improving the system.

Object-Based Image Analysis (OBIA) and Machine Learning (ML) Applied to Tropical Forest Mapping Using Sentinel-2

The purpose of this research was to distinguish and estimate natural forest areas at Paraná, Brazil. Forest plantations (Silviculture) and natural forests have high annual vegetative vigor, as well as agricultural areas in the periods of agricultural harvests, which can bring classification errors between these classes of Land Use and Land Cover (LULC), these classes have similar spectral signatures, but have a distinct texture that can be separated in the supervised classification process, with the joining of object and pixel-to-pixel classification method approaches. Thus, image segmentation techniques through Object-Based Image Analysis (OBIA) and Machine Learning (ML) made forest mapping possible over a large territorial extension. The Google Earth Engine (GEE) platform was used to calculate the vegetation indices (VIs) and Spectral Mixture Analysis (SMA) fraction spectral from Sentinel-2 images, and the creation of homogeneous spectrally shaped regions under supervised classification of phytoecological regions and mesoregions. The overall precision obtained in the mappings resulted in 0.94 Kappa Index (KI) and 96% of Overall Accuracy (OA), which indicates a high performance in large-scale forest mapping. The proposed dataset, source codes and trained models are available on Github (https://github.com/Cechim/simepar-brazil/), creating opportunities for further ad vances in the field.

Identifying the Determinants of the Increase in Native Forests in Southern Chile

In Chile, the native forest has suffered anthropic pressure that has resulted in the reduction in its surface and increased degradation, which has led to the development of public policies to reverse this scenario and encourage its sustainable management and conservation. This study examines the socioeconomic variables that influence the area increase in native forests in southern Chile, based on the analysis of 154 properties in the regions of Los Ríos, La Araucanía and Los Lagos. Georeferenced information from the 2015 SIMEF program survey and the Cadastre and Evaluation of Native Vegetation Resources of Chile were used. A Probit regression model was implemented, which associates a traceable increase in the native forest area with the variables regarding the owner: location, gender, age, schooling, management plan and technical advisory; and regarding the exploitation: farm size, percentage of native forest, scrub and forest plantations of the property and number of animal units. The econometric results show that smaller farms and those located in Los Lagos presented less probability of increasing their native forests. In the same way, an increase in the share of forest plantations area decreases the probability. Conversely, the scrub area share is related to the recovery of native forests in the sample. No significant effects of the variables associated with the implementation of management plans and technical assistance were found.

Using the Google Earth Engine cloud-computing platform to assess the long-term spatial temporal dynamics of land use and land cover within the Letaba watershed, South Africa

Population growth and environmental shifts have elevated the pressure on land use and cover (LULC), necessitating vital management and adaptive strategies to preserve the balance between ecosystem services and human well-being in watersheds. It's pivotal to understand the implications of human-induced shifts from natural to human-dominated surroundings This study utilized Google Earth Engine (GEE) to analyze 31 years of LULC changes in Letaba watershed. Using GEE's random forest, LULC classes were mapped with 93% to 99% accuracy across four timeframes (1990, 2000, 2010, and 2021). Trends revealed declining water bodies (-4%), bare surfaces (-2%), natural forest (-3%), and grassland (-3%), while shrublands, plantations, and built-up areas increased at annual rates of 41%, 24%, and 47% respectively. This transformation reflects population-driven shifts, necessitating adaptive strategies. Given the importance of plantations for income, embracing climate-smart agriculture could ensure long-term food and environmental security, thus addressing the evolving dynamics in Letaba watershed.

Мониторинг земель лесного фонда провинции Кон Тум Вьетнама по данным дистанционного зондирования Земли

In recent years, cloud computing technology has become increasingly useful and practical in many fields, including forestry. Monitoring forest dynamics throughout a relatively large area requires collecting a large amount of input data, and processing it is very complex and time-consuming. In this study, we demonstrated the potential of applying cloud computing technology in the Google Earth Engine platform, in conjunction with remote sensing data to monitor forest land changes in Kon Tum province, Vietnam. The use of the javascript editor on Google Earth Engine (GEE) automated the process of collecting and processing remote sensing data to meet the specified criteria, while saving time, effort, and computer resources. Computing the normalized difference vegetation index and classifying land cover types using the Random Forest machine learning method on the GEE platform also showed accuracy in representing the distribution of vegetation cover and evaluating the status and changes in forest areas in Kon Tum province. The study showed that the policies of Kon Tum province administration in recent years have had a positive impact on restoring natural forest areas and reducing resource losses. So, the application of remote sensing data on the cloud computing platform of Google Earth Engine is a promising method for conserving and managing forest resources in Kon Tum province and throughout Vietnam