Dense Vegetation Cover Research Articles

Vegetation cover effects on sediment concentration and overland flow under artificial rainfall intensity

Soil erosion depends on a number of factors including rainfall intensity, density of plant cover, and area cover. The objective of this study is to investigate the impact of these factors on flow velocity, overland flow regimes, sediment concentration, and absolute soil detachment. The soil used in this study was sandy remolded agricultural soil. The soil is packed in a tray of 1 m2 fixed on a slope of 3%; five different intensities were simulated under different vegetation cover (density and area). The results indicated that the overland flow velocity with vegetation cover was best described by polynomial function. The mean flow velocity varied from 0.021 to 1.244 m/s. Overland flow regime is subcritical and laminar. However, there are significant relationships between the vegetation cover density and sediment concentration and absolute soil detachment. The sediment concentration ranged from 1.38 to 5.65 kg/m3 whereas the absolute soil detachment ranged from 0.021?10-3 to 1.244?10-3 kg/m2/s. Finally, the vegetation cover presented a good protector to soil sediment from erosion.

Modelling the effect of density vegetation coverage and the occurrence of peridomestic infestation by Triatoma infestans in rural houses of northwest of Córdoba, Argentina.

To better understand the dispersion strategies of Triatoma infestans (Klug) (Hemiptera: Reduviidae, Triatominae), we evaluated the spatial effect of infested peridomicile and density vegetation cover in a historically endemic area for Chagas disease. The study was conducted in rural houses of the northwest of Córdoba province, Argentine, during 2012-2013. Active search of triatomines were made in domicile and peridomicile habitats. To characterize vegetation coverage, a thematic map was obtained considering five types of vegetation cover (closed/open forest, closed/open shrubland and cultural land). From each house we extracted the area of vegetation coverage, housing density and infested peridomiciles density. We used generalized linear models to evaluate the effect of these variables on the occurrence of infested peridomicile. According to our results, the probability of a peridomicile to be infested increases by 1.34 (95%CI [0.98; 1.90]) times more when peridomicile structures are in environments with higher housing density and by 1.25 (95%CI [0.84; 1.88]) more times when houses are surrounded by open shrublands. Among the multiple ecological determinants of peridomestic infestation, the influence of vegetation cover has been poorly studied. In this study we discussed the effect of the vegetation as a potential modulator of the dispersion strategies of T. infestans.

Количественные показатели и трофическая структура зоопланктона разнотипных участков мелководной зоны Мешинского залива Куйбышевского водохранилища

The trophic structure and quantitative characteristics of zooplankton in four shallow water areas of Meshinsky Bay of Kuibyshev Reservoir were studied in the summer and autumn seasons. The sites differed in their protection from wind and wave impacts, and in intensity of macrophyte overgrowth. The maximum species richness of zooplankters feeding in the water column was observed in open and vegetation-free shallow water and foraging from the surface of the substrate in closed areas, overgrown mainly with one type of submerged plant. The highest quantitative indicators of zooplankton in all areas were observed in summer. Regardless of the season, the maximum abundance and biomass of communities was observed in protected shallow water in thickets of Potamogeton lucens L. This is associated with the density of vegetation cover protecting invertebrates from predation by fish.

Normalized difference vegetation index analysis of the first part impacted with the breaking of the Fundão Dam in Mariana-MG

This paper addresses the exploitation of mineral resources and suggests that an environmental management that meets a set of measures and mutual cooperation between public and private managers, civil society, and mining companies that exploit natural, renewable, and non-renewable resources is needed. Cooperation between managers and joint safety measures can prevent present and future accidents like the one that occurred in Mariana City in Minas Gerais State (MG). The questioning presented puts into discussion the disaster that occurred in Mariana City due to the rupture of the ore tailings dam (Fundão dam) in November 2015. With an estimated population of 60,000 inhabitants, Mariana City has a local economy directly linked to mining activities. Due to the impact caused by the rupture of the Fundão dam, both city and vegetation were destroyed, among other factors observed along the path followed by the tailings. However, what is discussed in this article with greater emphasis is the loss of vegetation in the watershed. The methodology compared the degree of vegetation coverage in the basin area through the analysis of the Normalized Difference Vegetation Index – NDVI for 2013, 2016, 2017, 2018, and 2019 in different months. Some images refer to August and other samples are from September, complementing the process through the use of Landsat 8 satellite images - OLI sensor, acquired from the United States Geological Survey (USGS) repository. 299 points were distributed in the quadrant to perform the analyses (n = 299). The level of significance was set at 5% with a 95% confidence, to ascertain and verify whether the data distribution is in an acceptable condition (dense or semi-dense vegetation cover). Regarding vegetation analysis, the Kolmogorov-Smirnov and Shapiro-Wilk tests were used. Both tests indicated a non-normal distribution for the NDVI data set, which indicates the absence of a vegetation index that was covered by the tailings, resulting in an area with large spaces without the coverage previously registered in 2013. We conclude that the vegetation suffered a drastic alteration provoked by the rupture of the Fundão dam which also led to homeless residents, negative impacts on the livelihood of the small farmers and fishermen, silting up of rivers and streams, death of several animal and plant species, and also affected the ecosystem and the local and regional biodiversity.

Dust‐Drought Nexus in the Southwestern United States: A Proxy‐Model Comparison Approach

AbstractThe U.S. Southwest is naturally prone to dust and drought. With a high risk of unprecedented drought in the future due to climate change, changes in the dust cycle are expected. Whereas paleo records of dust deposition from the region suggest that past megadroughts did not coincide with elevated dust levels, modern studies indicate higher dust during drier conditions. To examine this disagreement, we compare regional paleo records to output from the Community Earth System Model Last Millennium Ensemble experiment. We investigate the role of hydroclimate on dust emissions in the model and analyze how modeled dust during megadroughts compares to all other years. We find that bare ground, as directly modulated by the density of vegetation cover and indirectly by hydroclimate, is the primary control on simulated dust emissions in the Southwest. Furthermore, we find slightly (but significantly) higher dust emission during megadroughts than during years without megadroughts in the model. Using a simple forward modeling approach to assess the impact of age uncertainty in the regional dust records, we find that age uncertainty can explain most of the paleo data/model disagreement. The remaining difference could be related to processes that are not included in the model that inhibit dust emissions during drought, including brown vegetation and soil crusts. Our results suggest the dust‐drought nexus is a continuum and that the impact of drought on dust cycling is subtle.

Differences in the bird community between a regenerating area and a native forest in Southeastern Brazil

ABSTRACT Restoration of degraded areas might be assessed via faunal communities of a particular region, and birds are one of the taxa most suitable in such assessments. This study evaluated the dynamics of a bird community in an area of Cerrado under natural regeneration, comparing it with one in the forest remnants. Birds were censused by a total of 24 point counts in both areas comprising 96 h of total sampling. Richness, abundance and diversity were greater at the regeneration area, possibly due to the heterogeneity of habitats, the consequent niche diversity, and the connectivity between patches of vegetation. Functional groups were also distinct between both sites, including species composition, feeding guilds and foraging strata. The regeneration site presented a higher abundance of omnivorous, granivorous and nectarivorous species, which might be related to the presence of sparser canopy, multiple opportunities for the development of grasses and forest-edge plants blooms in open areas. In contrast, higher abundance of invertebrate predators and frugivorous was found in the forested area, further confirming the relationship between those guilds and dense vegetation cover with closed canopies.

Detection and Monitoring of Post-Earthquake Landslides in Jiuzhaigou Using Radar Remote Sensing

Objectives On 8th August 2017, a catastrophic earthquake of Ms 7.0 struck the County of Jiuzhaigou in Sichuan Province, China. Because of its high magnitude and shallow epicenter, the earthquake caused grave casualties and property losses. Furthermore, the earthquake triggered numerous secondary mountain disasters such as rockfall and landslide. We use the synthetic aperture radar interferometry (InSAR) technique to detect post-earthquake landslides in Jiuzhaigou area. Methods Firstly, we carry out a quick detection across wide area using differential InSAR (DInSAR) technique with 6 ALOS-2 PALSAR-2 ascending images. DInSAR technique can observe the subtle deformation of landslide surface during the period between two SAR observations, so the active deforming landslides can be efficiently distinguished from stable areas. Nevertheless, the performance of DInSAR is often limited by temporal and spatial decorrelations induced by dense vegetation coverage, etc. To retrieve the temporal evolution of these landslides, detailed monitoring of specific landslides is carried out using time-series InSAR technique with 112 Sentinel-1 ascending and descending images. Time-series InSAR technique can overcome the limitation of traditional DInSAR technique in spatial-temporal decorrelation, and improve the deformation measurement accuracy. Therefore, the combination of DInSAR and time-series InSAR is adopted to accurately monitor single landslide, and efficiently detect landslides in Jiuzhaigou area. Results The results show that there are 13 landslides that can be detected by InSAR analyses in Jiuzhaigou area, including 7 landslides close to residential areas. The time series displacements retrieved indicate that several landslides have long-term linear deformations after the 2017 earthquake. These landslides severely threaten people's life and property and need to be monitored regularly. Finally, the reliability of detection results based on InSAR technology is verified by a field survey. Conclusions The results can provide key supports for the geohazard mitigation and prevention in the Jiuzhaigou scenic area. We indicate that a strategy which combines DInSAR technique with time-series InSAR can efficiently and accurately detect and monitor landslides over a wide area.

Mutual and Opposing Responses of Carabid Beetles and Predatory Wasps to Local and Landscape Factors in Vineyards.

Simple SummaryThe aim of this study was to contribute to closing knowledge gaps on managing vineyards and viticultural landscapes in order to support insect diversity and abundance. We studied two different groups of predating insects, carabid beetles and cavity-nesting wasps, in organically and conventionally managed vineyards in Germany. Effects of surrounding landscapes and vegetation structure within vineyards were evaluated. No differences in species richness and abundance of carabid beetles and cavity-nesting wasps were found between organic and conventional management. Enhanced vegetation cover was positively correlated with carabids and negatively with wasps. High covers of annual crops in the surrounding landscape led to fewer species and individuals of both groups. The results underline the importance of insect-friendly management, especially in intensely farmed landscapes.Preserving agro-biodiversity is one of the main means at the moment to counteract the global biodiversity crisis. Vineyard inter-rows offer vegetation covers which could function as foraging grounds for arthropods. Furthermore, organic management and enhanced landscape complexity often support biodiversity. Here, species richness and abundance of two groups of arthropod predators in vineyards were studied. Fifteen pairs of organically and conventionally managed vineyards were chosen along a gradient of landscape complexity in Rhine-Hesse, Germany. Carabid beetles were sampled using pitfall traps and cavity-nesting wasps with trap nests, respectively. Proportions of different land-use types surrounding the vineyards were calculated and inter-row vegetation cover was characterized. Species richness and abundances of both predator groups were not significantly affected by the management system. Likewise, increased cover of semi-natural habitats in the surrounding landscape did not promote their diversity or abundance. Instead, the increasing cover of annual crops diminished both groups. Cavity-nesting wasps profited from dense inter-row vegetation cover, while carabids were disadvantaged. The results indicate that distinct taxa within the same trophic group can respond oppositely to vineyard management. Thus, inter-row vegetation management with densely and sparsely vegetated elements might be best to support predator diversity. Overall, our results suggest that organic viticulture alone is insufficient to assist the studied insect groups, and that other local and landscape management options are needed for their protection.

Developing a framework to connect health equity energy, and green infrastructure for heat impacts mitigation in New York City

Background:Every summer, over 500 New Yorkers visit the emergency room for a heat related illness, and researchers estimate that over 100 excess deaths are associated with extreme heat events. In New York City (NYC), heat risks disproportionately impact under-privileged populations due to historical disinvestment in housing, neighborhood green infrastructure and air conditioning (AC) prevalence. Therefore, heat mitigation strategies must consider equity.Methods: In the summer of 2019, the NYC Department of Health, Mayor’s Office of Resilience, and NYC Parks conducted a comprehensive data collection campaign in heat vulnerable neighborhoods, as previously determined through an epidemiological analysis considering social and environmental factors. Data collection included: (1) outdoor air temperature measurements using ~35 sensors in every neighborhood; (2) indoor temperature measurements and surveys in 64 residential units and 9 libraries; and (3) energy consumption associated with AC use in 40 locations. We modeled outdoor afternoon (6-9 pm) and nighttime (3-5am) air temperature as a function of neighborhood land-use and vegetative cover. Indoor temperatures were characterized in relation to outdoor temperature, AC types and energy usage. Results: Indoor temperatures were lower in the units with ACs and correlated with the energy usage, but the type of AC and locational characteristics within the building modified these relationships. Outdoor temperatures were negatively associated with the density of vegetative cover (both grass/shrub and tree-canopy) and positively associated with impervious surfaces and building cover. Conclusions: Given that AC prevalence in some heat vulnerable neighborhoods is low (e.g., 75%), the immediate mitigation for thermal safety needs to consider providing and paying for AC in these neighborhoods. In addition, a substantial increase in vegetative cover would be needed to mitigate the projected future increase in outdoor air temperature in these neighborhoods.

Influence of Different Satellite Imagery on the Analysis of Riparian Leaf Density in a Mountain Stream

In recent decades, technological advancements in sensors have generated increasing interest in remote sensing data for the study of vegetation features. Image pixel resolution can affect data analysis and results. This study evaluated the potential of three satellite images of differing resolution (Landsat 8, 30 m; Sentinel-2, 10 m; and Pleiades 1A, 2 m) in assessing the Leaf Area Index (LAI) of riparian vegetation in two Mediterranean streams, and in both a winter wheat field and a deciduous forest used to compare the accuracy of the results. In this study, three different retrieval methods—the Caraux-Garson, the Lambert-Beer, and the Campbell and Norman equations—are used to estimate LAI from the Normalized Difference Vegetation Index (NDVI). To validate sensor data, LAI values were measured in the field using the LAI 2200 Plant Canopy Analyzer. The statistical indices showed a better performance for Pleiades 1A and Landsat 8 images, the former particularly in sites characterized by high canopy closure, such as deciduous forests, or in areas with stable riparian vegetation, the latter where stable reaches of riparian vegetation cover are almost absent or very homogenous, as in winter wheat fields. Sentinel-2 images provided more accurate results in terms of the range of LAI values. Considering the different types of satellite imagery, the Lambert-Beer equation generally performed best in estimating LAI from the NDVI, especially in areas that are geomorphologically stable or have a denser vegetation cover, such as deciduous forests.

Lateglacial and Holocene environmental history of the central Kola region, northwestern Russia revealed by a sediment succession from Lake Imandra

Bolshaya Imandra, the northern sub‐basin of Lake Imandra, was investigated by a hydro‐acoustic survey followed by sediment coring down to the acoustic basement. The sediment record was analysed by a combined physical, biogeochemical, sedimentological, granulometrical and micropalaeontological approach to reconstruct the regional climatic and environmental history. Chronological control was obtained by 14C dating, 137Cs, and Hg markers as well as pollen stratigraphy and revealed that the sediment succession offers the first continuous record spanning the Lateglacial and Holocene for this lake. Following the deglaciation prior to c. 13 200 cal. a BP, the lake's sub‐basin initially was occupied by a glacifluvial river system, before a proglacial lake with glaciolacustrine sedimentation established. Rather mild climate, a sparse vegetation cover and successive retreat of the Scandinavian Ice Sheet (SIS) from the lake catchment characterized the Bølling/Allerød interstadial, lasting until 12 710 cal. a BP. During the subsequent Younger Dryas chronozone, until 11 550 cal. a BP, climate cooling led to a decrease in vegetation cover and a re‐advance of the SIS. The SIS disappeared from the catchment at the Holocene transition, but small glaciers persisted in the mountains at the eastern lake shore. During the Early Holocene, until 8400 cal. a BP, sedimentation changed from glaciolacustrine to lacustrine and rising temperatures caused the spread of thermophilous vegetation. The Middle Holocene, until 3700 cal. a BP, comprises the regional Holocene Thermal Maximum (8000–4600 cal. a BP) with relatively stable temperatures, denser vegetation cover and absence of mountain glaciers. Reoccurrence of mountain glaciers during the Late Holocene, until 30 cal. a BP, presumably results from a slight cooling and increased humidity. Since c. 30 cal. a BP Lake Imandra has been strongly influenced by human impact, originating in industrial and mining activities. Our results are in overall agreement with vegetation and climate reconstructions in the Kola region.

Soil Moisture Estimation for the Chinese Loess Plateau Using MODIS-derived ATI and TVDI

Timely and effective estimation and monitoring of soil moisture (SM) provides not only an understanding of regional SM status for agricultural management or potential drought but also a basis for characterizing water and energy exchange. The apparent thermal inertia (ATI) and Temperature Vegetation Dryness Index (TVDI) are two widely used indices to reflect SM from remote sensing data. While the ATI-based model is routinely used to estimate the SM of bare soil and sparsely vegetated areas, the TVDI-based model is more suitable for areas with dense vegetation coverage. In this study, we present an iteration procedure that allows us to identify optimal Normalized Difference Vegetation Index (NDVI) thresholds for subregions and estimate their relative soil moisture (RSM) using three models (the ATI-based model, the TVDI-based model, and the ATI/TVDI joint model) from 1 January to 31 December 2017, in the Chinese Loess Plateau. The initial NDVI (NDVI0) was first introduced to obtain TVDI value and two other thresholds of NDVIATI and NDVITVDI were designed for dividing the whole area into three subregions (the ATI subregion, the TVDI subregion, and the ATI/TVDI subregion). The NDVI values corresponding to maximum R-values (correlation coefficient) between estimated RSM and in situ RSM measurements were chosen as optimal NDVI thresholds after performing as high as 48,620 iterations with 10 rounds of 10-fold cross-calibration and validation for each period. An RSM map of the whole study area was produced by merging the RSM of each of the three subregions. The spatiotemporal and comparative analysis further indicated that the ATI/TVDI joint model has higher applicability (accounting for 36/38 periods) and accuracy than the ATI-based and TVDI-based models. The highest average R-value between the estimated RSM and in situ RSM measurements was 0.73 ± 0.011 (RMSE—root mean square error, 3.43 ± 0.071% and MAE—mean absolute error, 0.05 ± 0.025) on the 137th day of 2017 (DOY—day of the year, 137). Although there is potential for improved mapping of RSM for the entire Chinese Loess Plateau, the iteration procedure of identifying optimal thresholds determination offers a promising method for achieving finer-resolution and robust RSM estimation in large heterogeneous areas.

Assessment of soil erosion patterns using RUSLE model and GIS tools (case study: the border of Khuzestan and Chaharmahal Province, Iran)

Soil erosion is one of the most prevailing forms of land degradation all over the world. The type and density of vegetation cover are effective on magnitude of soil erosion. The understanding of interactions between land use management, land cover, and topographical properties of landscape is important to effectively control soil erosion implementing best management practices. Regarding the influences of crop cover characteristics on soil erosion patterns; the presented study was conducted with the aim of evaluation of temporal soil erosion patterns affected by vegetation cover using revised universal soil loss equation (RUSLE) model. The study area is located in the border of Khuzestan and Chaharmahal Province, Iran, country with the geographical coordination of 31° 33′ 48′′ to 32° 25′ 40′′ N and 49° 50′ 44′′ to 50° 51′ 55′′ E. The input factors of RUSLE model including R, K, LS, and CP were generated using the Map algebra in ArcGIS 10.4 software. Afterwards, based on the real data, the 5 and 10 year forecasted of NDVI (normalized difference vegetation cover) was calculated and C-factor was estimated. Moreover, the spatial distribution of C-factor, canopy cover percentage (real and forecasted), Excess Greenness Index, Fractional Vegetation Index and NDVI* were mapped. Our results revealed that areas with the highest NDVI have the lowest C-factor with the lowest water erosion potential (R2 0.998). Also there was no remarkable difference between 5- and 10-year-forecasted C-factor in all studied stations because of no meaningful variations in the rainfall amount during this 5 years. Based on the Excess Greenness Index, the study area mostly is bared with a potential for soil erosion. The map of soil erosion distribution generated by RUSLE model depicted that the average amount of soil erosion was 13.68 tone/ha/year (STD 22.28), whereas for 10-year forecasted of soil erosion was 6.42 tone/ha/year (STD 9.80). Our mapping results illustrated that there was three main classes of soil erosion patterns including, the area with erosion mitigation, the area without change, and the area with increasing of soil erosion. These patterns confirmed that the vegetation cover distribution was different in the study area. Regarding the reduction of R-factor, the 10-year-forecasted soil erosion meaningfully decreased. Generally, the RUSLE model coupled with ArcGIS was capable to simulate soil erosion patterns and generate the spatial distribution map of erosion which is convenient visual tool to monitor and control of soil erosion. Furthermore, due to the variability of C-factor (temporal and spatial), therefore, more field experiments will be conducted for validating the C-factor forecasting using vegetation indices.

Monitoring soil carbon flux with in-situ measurements and satellite observations in a forested region

Carbon dioxide (CO2) flux plays a key role in the energy balance of ecosystems and effective monitor CO2 flux from soil at both large scale and high temporal resolution remains a critical scientific problem of soil science. To address this scientific problem, this study tested a novel model to estimate CO2 flux from soil with highly dense vegetation cover. In contrast to previous approaches, the developed model monitored daily CO2 flux at both high spatial and temporal resolutions. This model is applicable for different forest types by fusing the daily TERRA Moderate Resolution Imaging Spectroradiometer (MODIS), Land Remote Sensing Satellite (Landsat) measurements, and monthly in-situ CO2 flux measurements collected by non-permanent chambers in the Great Dismal Swamp (GDS), the U.S. Then, daily vegetation index and surface soil temperature were estimated at high spatial resolution, and the CO2 flux was retrieved through a semi-empirical model. Two-year ground observations in the GDS were used to train and validate the model. Over the GDS area, the validation results of the retrieved CO2 flux had a coefficient of determination (R2) of 0.47, and a root mean square error (RMSE) of 1.25e + 05 μg CO2/m2/h. Further analysis showed that the performance of the proposed method varied slightly with forest types. The difference between R2 was less than 0.07 and the difference between RMSE was less than 0.08e + 05 μg CO2/m2/h. The GDS has three main forest types: maple gum (Acer rubrum and Nyssa sylvatica), Atlantic white cedar (Chamaecyparis thyoides), and pine pocosin (Pinus serotina). For the maple-gum, the R2 was 0.51, and the RMSE was 1.14e + 05 μg CO2/m2/h. For Atlantic white cedar, the R2 was 0.62, and the RMSE was 1.15e + 05 μg CO2/m2/h. For pine pocosin, the R2 was 0.44, and the RMSE was 1.07e + 05 μg CO2/m2/h. The proposed method enables estimation of CO2 flux within forested areas, and forest type affects the monitoring results.

Intermittent percolation and the scale-free distribution of vegetation clusters

Understanding the causes and effects of spatial vegetation patterns is a fundamental problem in ecology, especially because these can be used as early predictors of catastrophic shifts such as desertification processes. Empirical studies of the vegetation cover in some areas such as drylands and semiarid regions have revealed the existence of vegetation patches of broadly diverse sizes. In particular, the probability distribution of patch sizes can be fitted by a power law, i.e. vegetation patches are approximately scale free up to some maximum size. Different explanatory mechanisms, such as plant–plant interactions and plant-water feedback loops have been proposed to rationalize the emergence of such scale-free patterns, yet a full understanding has not been reached. Using a simple model for vegetation dynamics, we show that environmental temporal variability—a well-recognized feature of semiarid environments—promotes in a robust way (i.e. for a wide range of parameter values) the emergence of vegetation patches with broadly distributed cluster sizes. Furthermore, this result is related to a percolation phenomenon that occurs in an intermittent or fluctuating way. The model also reveals that the power-law exponents fitting the tails of the probability distributions depend on the overall vegetation-cover density, in agreement with empirical observations. This supports the idea that environmental variability plays a key role in the formation of scale-free vegetation patterns. From a practical viewpoint, this may be of importance to predict the effects that changes in environmental conditions may have in real ecosystems. From a theoretical side, our study sheds new light on a novel type of percolation phenomena occurring under temporally-varying external conditions, that still needs further work to be fully characterized.

Gaussian processes retrieval of LAI from Sentinel-2 top-of-atmosphere radiance data

Retrieval of vegetation properties from satellite and airborne optical data usually takes place after atmospheric correction, yet it is also possible to develop retrieval algorithms directly from top-of-atmosphere (TOA) radiance data. One of the key vegetation variables that can be retrieved from at-sensor TOA radiance data is leaf area index (LAI) if algorithms account for variability in atmosphere. We demonstrate the feasibility of LAI retrieval from Sentinel-2 (S2) TOA radiance data (L1C product) in a hybrid machine learning framework. To achieve this, the coupled leaf-canopy-atmosphere radiative transfer models PROSAIL-6SV were used to simulate a look-up table (LUT) of TOA radiance data and associated input variables. This LUT was then used to train the Bayesian machine learning algorithms Gaussian processes regression (GPR) and variational heteroscedastic GPR (VHGPR). PROSAIL simulations were also used to train GPR and VHGPR models for LAI retrieval from S2 images at bottom-of-atmosphere (BOA) level (L2A product) for comparison purposes. The BOA and TOA LAI products were consistently validated against a field dataset with GPR (R2 of 0.78) and with VHGPR (R2 of 0.80) and for both cases a slightly lower RMSE for the TOA LAI product (about 10% reduction). Because of delivering superior accuracies and lower uncertainties, the VHGPR models were further applied for LAI mapping using S2 acquisitions over the agricultural sites Marchfeld (Austria) and Barrax (Spain). The models led to consistent LAI maps at BOA and TOA scale. The LAI maps were also compared against LAI maps as generated by the SNAP toolbox, which is based on a neural network (NN). Maps were again consistent, however the SNAP NN model tends to overestimate over dense vegetation cover. Overall, this study demonstrated that hybrid LAI retrieval algorithms can be developed from TOA radiance data given a cloud-free sky, thus without the need of atmospheric correction. To the benefit of the community, the development of such hybrid models for the retrieval vegetation properties from BOA or TOA images has been streamlined in the freely downloadable ALG-ARTMO software framework.

A Model to Estimate Stored Carbon in the Upland Forests of the Wanggu Watershed

Climate change coupled with deforestation has brought about an increase in greenhouse gas emissions in the atmosphere. One way to control climate change is to reduce greenhouse gas emissions by maintaining the integrity of natural forests and increasing the density of tree populations. This research aimed to (a) identifies the density of stand trees in the upland forests of the Wanggu Watershed; (b) analyze the potential carbon stocks contained in the upstream forests of the Wanggu Watershed; (c) develop a model to estimate potential carbon stocks in the upland forests of the Wanggu Watershed. The land cover classification in this study used the guided classification with the Object-Based Image algorithm. Normalized Difference Vegetation Index (NDVI) was employed as an indicator of vegetation cover density. Field measurements were carried out by calculating the diameter of the stand trees in 30 observation plots. Field biomass values were obtained through allometric equations. Regression analysis was conducted to determine the correlation between NDVI densities and field biomass. The results showed that the best equation for estimating potential carbon stocks in the Wanggu Watershed forest area was y = 3.48 (Exp. 7,435x), with an R2 of 50.2%. Potential above ground biomass carbon in the Wanggu Watershed based on NDVI values was 414,043.26 tons in 2019, consist of protected forest areas of 279,070.15 tons and production forests of 134,973.11 tons. While total above biomass carbon based on field measurement reached 529,541.01 tons, consist of protected forests of 419,197.82 tons and production forests of 110,343.20 tons.

Investigation of the impacts of urban vegetation loss on the ecosystem service of air pollution mitigation in Karaj metropolis, Iran.

The present study aims to investigate the relationship between reduced air pollution and ecosystem services in Karaj metropolis, Iran. To the end, the trends in the concentrations of O3, NO2, CO, SO2, PM10, and PM2.5 as the main atmospheric pollutants of Karaj were studied. Five time series models of autoregressive (AR), moving average (MA), autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA), and seasonal autoregressive integrated moving average (SARIMA) were used to predict changes in air pollutant concentrations. Air pollution zoning is conducted via ArcGIS10.3 by using spline tension interpolation method. Then, normalized difference vegetation index (NDVI) was obtained from Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images to analyze vegetation dynamics as an index of ecosystem functioning. NDVI thresholds were selected to present guidelines for qualitative and quantitative changes in green cover and were divided into five different categories. Based on the results, AR (1) and ARIMA (1,2,1) were recognized as appropriate models for predicting the concentration of air pollutants in the study area. A decrease in very dense vegetation coverage and increase in poor vegetation areas, followed by an increase in air pollution, revealed that the loss of urban green coverage and decreased ecosystem services were positively related. Furthermore, the expansion of urban lands toward the north and the west from the baseline to future condition led to great changes in the land cover and losses in vegetation along these axes, which finally resulted in increased air pollution in these areas. Thus, the results of this study can be directly used in decision-making in the area of air pollution.

CREATING AN INFORMATIVE CARTOGRAPHIC MODEL OF THE REGION TO ASSESS THE STATE OF ITS BIORESOURCES

The aim of the work is to create an informative map model of the region in order to monitor changes in the quality and density of vegetation cover in the NRin the period from 2010 to 2019 using the NDVI index. The month of observations for July, as the middle of the vegetation period of vegetation in this region. After determining the NDVI index, it is necessary to search for phenomena that affect the quality and level of vegetation of the NSO. Factors affecting the quality and constancy of energy sources are a source of energy from road transport, the total amount of waste, the average temperature for the observation period, and forest. for the period of observation and the period preceding, the species composition of forest stands. The main problem is the search, obtaining statistical data for the search period, research, the possibility of cartographic presentation of data, the search for the relationship between phenomena using mathematical research methods. The result of the research is a map showing the relationship between the NDVI index and the factors influencing it, based on which we can draw conclusions about the dynamic changes in the quality of life over 9 years and present the dynamics of future changes.

Legacy effects of sika deer overpopulation on ground vegetation and soil physical properties

Long-lasting overpopulation of deer can prevent or retard the recovery of ground vegetation of forests even after overpopulation would have abated. This persistent impact, or legacy effect of deer, would be explained by hypothetical mechanisms such as limitation of seed sources, dominance of competitors that are unpalatable to deer, and negative feedback from soil conditions degraded by direct and indirect effects of deer. So far, however, little evidence is available for existence of such legacy effects. To detect the legacy effects caused by sika deer (Cervus nippon) and reveal their possible mechanisms, we studied ground vegetation and soil condition of Japanese natural broad-leaved forests and cedar plantations, which have records of vegetation surveys of the past 11 years. Foliar cover and species composition of ground vegetation were analyzed together with the deer density index (DDI), which represents mean deer density of the last 9 years before the survey. The relationship between vegetation cover and deer density had significantly changed between the survey years, as was proved by a regression analysis. The cover of ground vegetation did not increase during the 11 surveyed years even at most study sites whose DDI value had decreased, thereby indicating the existence of legacy effects. This delay of recovery was not attributable to the dominance of unpalatable plants, which had slightly decreased during the 11 surveyed years. Palatable plants did not increase in most study sites where DDI decreased, suggesting seed source limitation. Negative indirect effects of DDI on soil physical property in the present, such as increased bulk density and decreased coarse porosity, were detected through structural equation modeling (SEM) analysis. In the case of broad-leaved forests, the SEM model that included the 2005 DDI values showed better performance than that using present DDI values, indicating a strong legacy of past deer impact. These facts suggest the existence of legacy effects, which possibly have been caused by seed source limitation and degraded soil conditions. Moreover, above statistical analyses showed that canopy closure, which can be caused by delayed management practices (e.g., gap creation and thinning), further limited recovery of vegetation. Ground vegetation of broad-leaved forests were suggested to show lower resilience than those of cedar plantations, requiring conservation activities such as canopy gap creation.