Percentage Of Vegetation Cover Research Articles

Mapping and dynamic monitoring of military training-induced vegetation cover loss using Sentinel-2 images and method comparison.

Sustainable management of the US Army installations is critical for military training and readiness of forces. However, monitoring military training-induced vegetation cover disturbances using remote sensing data is challenging due to the lack of methodology for optimizing the selection of spectral variables or predictors and spatial modeling methods. This study aimed to propose and demonstrate a methodological solution for this purpose. The study was conducted in the Fort Riley installation in which three training areas were selected to map and monitor the training-induced vegetation cover loss. Sentinel-2 images and field observations of percentage vegetation cover (PVC) were combined at a spatial resolution of 10m by 10m to map PVC and its dynamics by comparison of two predictor selection methods and five spatial modeling algorithms based on a total of 304 spectral variables from the images before and after the training. Results showed that overall, the correlation-based predictor selection method reduced the relative root mean square error (RRMSE) of PVC predictions by 4.44% than the random forest (RF)-based predictor selection. Machine learning methods including RF, neural network, and support vector machine overall reduced the RRMSE of PVC predictions by 42.83% compared with multiple linear regression and k-nearest neighbors. Combining correlation-based predictor selection and RF modeling, coupled with leave one out cross validation, provided the greatest potential of increasing the accuracy of monitoring the vegetation cover loss. The findings provided useful implications to develop a near real-time system of monitoring military training-induced vegetation cover loss.

Spatial analysis of vegetation using GIS and remote sensing data

The agricultural sector is one of the most important sectors in Iraq, as it supports the Iraqi economy and provides food security for people in Baghdad. Nevertheless, this sector is suffering from a remarkable decrease in agricultural production. Therefore, there is a high need for the assessment of the agricultural cover in the last decades to provide a comprehensive view of the changes in this sector. The research focuses on the spatial analysis of spatial and urban cover using GIS, remote sensing data, and the NDVI indicator in three periods of time (2001, 2011, and 2021). The results of the study showed a decrease in the area of vegetation cover for the year 2011 for most of the counties while the area of vegetation cover increased in the study area in 2021 in comparison with 2011 due to the impact of the water resources factor and the share of each county. In 2001, the percentage of vegetation cover was 37% of the study area while it was 23% in 2011 and increased to 32% in 2021. This research supports the decision-makers and planners by providing the amount and spatial distribution of the vegetation cover.

Evaluating the impacts of Payment for Ecosystem Services (water supplies) in an agricultural system of the Brazilian Cerrado.

In this study, we investigated the effects of the Payment for Ecosystem Services (PES) in an agrisystem located in the Brazilian Midwest. This PES benefits the owners of rural properties that encompass springs that feed the Abóbora River microbasin which supplies water for consumption in the city of Rio Verde, Goiás. We evaluated the percentage of native vegetation cover around the springs of the watercourses and also estimated its change over time (2005, 2011 and 2017). The vegetation cover of the Areas of Permanent Preservation (APP) increased by 2.24% on average, seven years after the implantation of the PES. There was little difference in the change of vegetation cover maintained over the study years (2005, 2011, and 2017), however, the vegetation cover increased for 17 springs, decreased for 11 springs, and was completely degraded for other two. To improve the performance of this PES, we recommend (1) expanding the program to include the APPs surrounding the springs, together with the legal reserves of each property, (2) implementing measures to ensure that properties are environmentally adequate, (3) including the properties in the Brazilian Rural Environment Register (CAR), and (4) obtaining environmental licensing for the activities undertaken within the Abóbora River basin.

Soils with more clay and dense vegetation were rich in soil carbon along Wadi Al-Sharaea, Makkah, Saudi Arabia

In arid ecosystems, lack of vegetation and nutrients can negatively impact soil carbon (C) content. In the current study, our goals were to assess soil C stocks to a depth of 50 cm in an arid ecosystem (Wadi Al-Sharaea, Saudi Arabia) and determine their relation to different vegetation cover. To address our research objective, a total of 102 quadrate (randomly selected) were established along the desert wadi. Soil samples were collected to a depth of 50 cm with 5 cm interval, then Soil Bulk Density (SBD, g/cm3), Soil Organic C Content (SOC, g C/kg), and stocks (kg C/m2) were estimated. Both soil mechanical and chemical analyses were conducted for a composite soil sample. Study sites were categorized based on their visual vegetation cover (VC) percentage (%) into three major groups: 1) scarce vegetation cover (VC less than 25%); 2) medium vegetation cover (VC is higher than 25% and less than 75%); and lastly 3) dense vegetation cover (VC is higher than 75%). Soils were characterized by higher sand content (48.2%, both fine and coarse compiled) than silt (36.7 ± 1.64%) or clay (10.1 ± 1.28%). There were significant differences among soil Calcium (Ca) and Potassium (K) content (p < 0.05), while those plant communities with medium vegetation cover showed the highest soil content of Ca and K (1.7 ± 0.24 and 0.2 ± 0.03 meq/l, respectively). Plant communities with dense vegetation cover had the lowest SBD (1.96 ± 0.03 g/cm3) and the highest SOC stocks (14.9 ± 2.1 kg C/m2). Moreover, our data analyses indicated that SBD and SOC content had strong and negative correlation, where soils with dense vegetation cover had the most significant correlation (R2 = 0.95). Our results recommend that soil carbon stocks to a depth of 50 cm based on different vegetation cover of arid ecosystems should be implemented on global soil carbon budget to better elucidate factors controlling SOC content at the regional and global scales.

Selection of inter-row herbaceous covers in a sloping, organic, non-irrigated vineyard.

Inter-row vegetation in vineyards is classified as a service crop as it provides many ecosystem services. The vegetation is often removed but maintaining them can mitigate the negative effects on the environment. However, the type of species or mixture choice can affect their success. A field trial was conducted in an organically-managed vineyard of Cabernet sauvignon Vitis vinifera L. cultivars in north-eastern Italy, in which three blends of grass species (Shedonorus arundinaceus, Lolium perenne and Festuca rubra) and two grass-legume mixtures were grown in the inter-rows and compared with resident vegetation and regularly tilled bare soil. Each vegetation type, including resident vegetation, was subjected to mulching and non-mulching treatments. The aim of this study was to evaluate the use of seeded species or mixtures in the inter-row spaces of the vineyard in north-Italy as an alternative management to resident vegetation and tilled soil. The experiment was conducted over two years to monitor the persistence of the sown vegetation and the influence of vegetation types on vine performance and grape composition, and on soil compaction and erosion. The relative abundances of each species, vegetation height, percentage green cover and normalised difference vegetation index (NDVI), vine shoot length, number of leaves per vine shoot, leaf area, bunch weight, vine NDVI, soil compaction and erosion, and depth and width of tractor tyre prints were measured. Over time, weed invasion altered the botanical composition of all vegetation types except for the S. arundinaceus blend, which remained stable throughout the study period. Our results showed that vine parameters were not affected by the type of vegetation in the inter-rows, nor were there differences between the grassed and bare soil inter-rows. Soil compaction and erosion, and tractor tyre prints were not directly affected by the type of vegetation cover, but they were affected by tillage in the plots with bare soil in the inter-rows or where it was used to prepare the soil for sowing. Soil compaction and erosion were related to the percentage vegetation cover. Mulching did not affect any of the parameters measured. Therefore, species selection plays a crucial role in inter-row vegetation management and in minimising environmental impacts. S. arundinaceus gave high protection against soil erosion due to its high persistence throughout the year and had the lowest growth rate thus requiring fewer cuttings.

Land use effects on the co-occurrence patterns of streams ichthyofauna in the eastern Amazon

In this manuscript, we aimed to answer: 1) which environmental and spatial processes are determinant for the patterns of co-occurrence of fish in Amazonian streams, and 2) which variables are responsible for the positive and negative associations between species pairs. For this, we sampled 32 Terra-Firme forest streams in a basin affected by different land uses in the eastern Amazon. In each stream, we measured environmental metrics for its physical characterization; estimated the percentage of land cover of the drainage network; and sampled the ichthyofauna. We also analyzed associations (positive or negative) between pairs of species and whether these associations were determined by physical habitat characteristics and the percentage of vegetation cover, spatial dispersal or biotic interactions, using a classical null model approach complemented by spatial tests and of environmental characteristics of the sites occupied by members of each pair of species. Most of the patterns of ichthyofauna co-occurrence occurred at random, composed mainly of rare species, which may be due to the specificity of these species or because the still forested and highly heterogeneous areas of the region may be acting as a mosaic, together with less aggressive land uses such as agriculture, generating these random pairs. Meanwhile, 32 species (41.03%) formed 613 non-random aggregated or segregated pairs (20.41% of the total pairs), composed mainly of species of intermediate frequency and abundance in the region and with different niches and guilds and determined by biotic interactions, environmental filters’ action and/or by limiting species dispersal.

What state of the world are we in? Targeted monitoring to detect transitions in vegetation restoration projects.

Monitoring vegetation restoration is challenging because monitoring is costly, requires long-term funding, and involves monitoring multiple vegetation variables that are often not linked back to learning about progress toward objectives. There is a clear need for the development of targeted monitoring programs that focus on a reduced set of variables that are tied to specific restoration objectives. In this paper, we present a method to progress the development of a targeted monitoring program, using a pre-existing state-and-transition model. We (1) use field data to validate an expert-derived classification of woodland vegetation states; (2) use these data to identify which variable(s) help differentiate woodland states; and (3) identify the target threshold (for the variable) that signifies if the desired transition has been achieved. The measured vegetation variables from each site in this study were good predictors of the different states. We show that by measuring only a few of these variables, it is possible to assign the vegetation state for a collection of sites, and monitor if and when a transition to another state has occurred. For this ecosystem and state-and-transition models, out of nine vegetation variables considered, the density of immature trees and percentage of exotic understory vegetation cover were the variables most frequently specified as effective to define a threshold or transition. We synthesize findings by presenting a decision tree that provides practical guidance for the development of targeted monitoring strategies for woodland vegetation.

Prediction of leaf area index using thermal infrared data acquired by UAS over a mixed temperate forest

• LAI prediction accuracy improves by integrating remote sensing VNIR and TIR data. • The relationship between LAI and LST is found to be insignificant. • LSE has a positive correlation with LAI. • Accurate measurement of the percentage of vegetation cover is crucial for LSE retrieval accuracy. • LAI prediction accuracy is higher with LST retrieved from a lower flight altitude. The leaf area index (LAI) is a crucial biophysical variable for remote sensing vegetation studies. LAI estimation through remote sensing data has mostly been investigated using visible and near-infrared (0.4–1.3 μm, VNIR) and Shortwave Infrared (1.4–3 μm, SWIR) data. However, Thermal Infrared (3–14 μm, TIR) data for LAI retrieval has rarely been explored. This study aims to predict LAI by integrating VNIR and TIR data from Unmanned Aerial Systems (UAS) in a mixed temperate forest, the Haagse Bos, Enschede, the Netherlands. The VNIR and TIR images were acquired in September 2020, in conjunction with fieldwork to collect LAI in situ data for 30 plots. TIR images were acquired at two heights (i.e., 85 m and 120 m above ground) to investigate the effect of flight height on the LAI prediction accuracy by means of UAS data. Land Surface Temperature (LST) and Land Surface Emissivity (LSE) were computed and extracted from the collected images. LAI was estimated using seven vegetation indices and Partial Least Squares Regression (PLSR). LAI prediction accuracy using VNIR reflectance spectra was compared to the accuracy achieved by integrating VNIR data with LST or LSE applying vegetation indices as well as PLSR. Among the applied vegetation indices, the Reduced Simple Ratio (RSR) gained the highest prediction accuracy using VNIR data (R 2 = 0.5815, RMSE = 0.6972); the prediction accuracy was not improved when LST was integrated with VNIR data but increased when LSE was included (RSR: R 2 = 0.7458, RMSE = 0.5081). However, when LST from 85 m altitude and VNIR data was applied as an input using PLSR (R 2 = 0.5565, RMSE CV = 0.7998), the LAI prediction accuracy was slightly increased compared to when only VNIR data was used (R 2 = 0.4452, RMSE CV = 0.8668). Integrating VNIR data with LSE significantly improved the LAI retrieval accuracy (R 2 = 0.7907, RMSE CV = 0.8351). These findings corroborate prior research indicating that combining LSE with VNIR data can increase the prediction accuracy of LAI. However, LST was found to be ineffective for this purpose. The relationship between LAI and LSE should be the subject of more investigation through various approaches to bridge the existing scientific gap.

NEIGHBORHOOD GREEN SPACE IS ASSOCIATED WITH INCREASED CONNECTEDNESS TO NATURE IN ADULTS AND OLDER PEOPLE

Introduction: The evidence suggests that natural environments are essential for sustainable urban development, for the quality of life and well-being of the population, through improved health and physical activity (PA). However, the relationship between the connectedness to nature (CN), the percentage of vegetation cover in the neighborhood, and levels of PA still need further investigation. Purpose: The current study examines the associations between residential green space, PA, and CN in subjects between the ages of 18 and 75 years. Methods: The sample included 194 individuals, 61 men (41.42±15.37 years) and 133 women (39.93±15.60 years). Green space coverage (%) was appreciated through the Simplified Land Occupation Map. Total PA, moderate-vigorous physical activity (MVPA), and steps/day were measured using triaxial accelerometers (wGT3X-BT) which were worn on the non-dominant wrist for 4 consecutive days. Levels of MVPA ≥150 min/week and steps/day ≥10 000 were considered recommended and the Connectedness to Nature Scale was applied. The data were analyzed using the Student’s T test or the Mann-Whitney U test. For one of the analyses, a cutoff value of 44 years was considered, based on the division into two groups with equal numbers of observations. We also performed Pearson’s correlation and partial correlation analyses. Statistical significance was set at p ≤0.05. Results: The sample belonged to an area with high vegetation cover (71.51±15.15%) and exhibited a medium-high affective relationship with nature (3.73±0.43 points). The MVPA levels and steps/day identified in each gender were within the values recommended in the literature (182.75 ± 110.24 min/week and 13166.23± 3843.36 steps/day in men and 175.86±118.84 min/week and 125886.14±3783.46 steps/day in women). No statistically significant differences were identified between the two genders in relation to age, physical activity, green space coverage and connectedness to nature. In both genders, age showed a positive association with CN (r=0.303 in men and r=0.277 in women, p ≤0.05). In women, a significant correlation was also identified between age and the green area (r=0.286, p ≤0.01). Our results also indicated that in both genders, living in an area with high vegetation cover contributes to a greater affective and experiential connection with nature (r=0.426 for men and r=0.107 for women, p ≤0.05). Controlling for age this association in men was 0.390 for p ≤0.01 with a confidence of 15.2%. In women this association lost statistical significance with age control. Concerning the variables evaluated by accelerometry, we identified only in women a relationship between the CN and the number of daily steps (r=0.189, p ≤0.05). In both genders, the results also revealed that individuals aged 44 or older were those who exhibited a higher CN and performed a greater number of daily steps compared to individuals aged ≤44 years. Conclusions: Our results suggest that older individuals and those living in areas with a high percentage of vegetation cover exhibited greater affective connection with the natural environment. Women more connected to the natural environment and live in areas with greater vegetation cover tend to be more active, performing a greater number of daily steps. Funding: This work is supported by National Funds by FCT-Portuguese Foundation for Science and Technology, under the projects UIDB/04033/2020, UID04045/2020 and UIDB/00073/2020. The investigation was also supported by European funding program Interreg Atlantic Area, under the project (EAPA_772/2018-Triple-C).

The interacting effects of irrigation, sowing date and nitrogen on water status, protein and yield in pea (Pisum sativum L.)

Management for agronomic practices might improves growth and grain yield in pea. The main objective of this experiment was to assess the interacting effects of different irrigation regimes, sowing date and nitrogen fertilizer treatments on pea traits. We evaluated three irrigation regimes (50, 75, and 100% of the plant irrigation requirement), two sowing dates (February and March), and nitrogen [application of nitroregn (N1) and without nitrogen as control (N0)] in 2019 and 2020 under field conditions. Chlorphyll content, leaf area index, leaf water potential, grain yield and water productivity were higher in the late sowing (March) than in early sowing (February) treatment. Percentage of vegetation cover in late sowing (60%) was significantly higher than in early sowing (52.7%) treatment. Grain yield in 75% water requirement treatment was not significantly different from yield in full irrigation treatment. Application of nitrogen fertilizer significantly reduced grain yield, grain protein and seeds per pod whilst increased chlorophyll content only. The 100% irrigation requirement treatment showed higher evaporation form the soil in N0 than in 50% and 75% irrigation treatments in late sown pea. Leaf evapotranspiration (ET) was lower in 50% water requirement irrigation regime than in the other irrigation treatments. Water use efficiency (WUE) which was higher in the late than early sowing treatment did not differ between 50% and full irrigation treatments in N0. In conclusion, the results of the current study suggested that application of nitrogen fertilizer did not benefit pea growth and that management of irrigation regime in late sowing might improve grain yield in pea and save irrigation water in regions with limited water availability.

Plant growth promoting microorganisms (PGPM) as an eco-friendly option to mitigate water deficit in soybean (Glycine max L.): Growth, physio-biochemical properties and oil content

Drought, as an important challenge in Iran, affects all growth indicators for plants. Application of plant growth promoting microorganisms (PGPM) can reduce the detrimental effects of water deficit on plants. Two separate field experiments were conducted at the Tehran and Hashtrood sites, Iran in 2019 to study the influences of Azotobacter chroococcum (Az) and Piriformospora indica (Pi) or Az + Pi on growth, physio-biochemical properties and oil content of soybean (Glycine max L.) under water deficit conditions. Although water deficit dramatically reduced the plant height, percent vegetation cover and relative water content (RWC), plots treated with Az and Pi exhibited higher performance mentioned traits at both sites. Besides, co-inoculation of Az and Pi increased proline in Tehran (48.85 and 29.24% in leaf and root, respectively) and Hashtrood (46.91 and 48.91% in leaf and root, respectively) under severe water deficit. Accumulation of glycine betaine, soluble sugars and proteins increased for plots which received Az and Pi. Under severe water deficit conditions, the co-inoculation with Az and Pi enhanced the oil content of soybean by 12.87 and 9.37% at Tehran and Hashtrood sites respectively. Application of Az and Pi resulted in reducing the adverse effects of water deficit on oil quality of soybean by increasing the linoleic and linolenic acid in oil. Moreover, inoculation of soybean with Az and Pi can provide drought tolerance by improving ascorbate peroxidase (APX), catalase (CAT), superoxide dismutase (SOD) and peroxidase (POX) activity. However, co-inoculation with Az and Pi was generally more effective in the alleviation of water deficit detrimental effects than sole inoculation with Az and Pi. Consequently, it can be a good approach for improving tolerance, growth and oil production of soybean under water deficit conditions.

ASSESSMENT OF STREAM ENVIRONMENTAL CONDITION USING FISHBASED METRICS IN A PROTECTED AREA AND ITS DISTURBED BUFFER ZONE, NORTHEASTERN ATLANTIC RAINFOREST

The susceptibility of streams to anthropogenic interference raises the need for continuous assessment of their environmental condition. From early studies to recent approaches, metrics derived from fish assemblages have proven to be fundamental tools in evaluating the ecological condition of watercourses. We assessed the environmental degradation of streams inside and surrounding the Córrego Grande Biological Reserve, state of Espírito Santo, Brazil, to develop and apply a biotic index for this region based on fish metrics. We performed samplings in 19 stream sites along 2012, 2018 and 2019, and collected 24 species belonging to five orders, 11 families, and 21 genera. The sites were classified as least-disturbed (N = 9, all within the protected area), intermediate (N = 8), and most-disturbed (N = 2). Ordination analyses distinctly separated the sites according to their disturbance classes, revealing that the percentage of native vegetation cover in 100 m buffers and type of riparian vegetation played an important role in the environmental quality of these sites. From the initial 38 metrics, three were able to distinguish between disturbance classes: percentage of Siluriformes and Characiformes species, percentage of nektonic species, and percentage of omnivorous individuals. Our results show that these metrics are significant factors to be considered in monitoring the environmental degradation of Atlantic Forest streams.

Analysis of the extent of the change of vegetation cover area in the heights of the southern Jordanian Mazar District for the period (1984-2021) using the vegetation coverage index (NDVI).

The study aimed to measure the change in the level of vegetation cover in the Southern Mazar District for the years (1980-2021), using the vegetation coverage index in the GIS program, and remote sensing data from available satellite visuals covering the study area for the time period. The study followed the applied analytical digital approach, and the tools of the geographic information systems program. The study found that the study area witnessed a significant decline in the area of ​​vegetation cover for the period between 1984 and 2021 AD, as follows: • The study area witnessed a clear decline in the area of ​​vegetation cover, in 1984 AD the percentage of vegetation cover was 89.4% of the area of ​​the study area, while in 2021 it decreased to 48%. • The decline in natural vegetation cover was significantly related, according to the vegetation cover index, to the annual rainfall rate. In 1984 AD, the area of ​​vegetation cover was 334.9 km2, and the annual rainfall amounted to 468 mm for the same year, while the area of ​​land covered by vegetation decreased to 190 km2 when the amount was Annual rainfall of 137 mm in 2021. • The arid climate characteristics extend from the desert and semi-desert region on the eastern side towards the mountainous region on the western side. • The impact of urbanization significantly on the decline of vegetation cover areas in the study area in general, and in the areas of the shrine, Mu'ta and Moab in particular due to the increase in the urban area, and the estimated amount of decline in the area of ​​vegetation cover is about 1.1 km² annually. Finally, the study recommended the necessity of taking quick and decisive measures by the decision maker to reduce the severity and speed of the decline of vegetation cover in the eastern parts of the study area, and to expand the study of the most affected species of natural plants to address the problem early.

Legal reserves ensure alpha and beta ant diversity in highly modified agricultural landscapes

To preserve biodiversity, the Brazilian law postulates that rural properties must keep a percentage of native vegetation cover, denominated as “Legal Reserve” (LR). Recent political efforts are being made to disoblige the farmer to keep the LRs. In this study we evaluated the role of LRs in ensuring the ant biodiversity on LRs and soybean plantations. Ants were collected in 42 landscapes within Amazonian forests and Cerrado savannahs and the transition vegetation between them. In each landscape, sets of pitfall traps were placed in a paired design, in the Legal Reserve area and in the adjacent soybean cultivation matrix. As expected, the number of species was extremely lower on soybean plantations. Despite richness, we observed strong turnover between the LRs and plantations. The landscape types on which the Legal Reserve was inserted did not influence the number, but did influence the composition of species. Also, the similarity among samples decay with geographic distance only on LRs. Our results show the importance of the maintenance of Legal Reserve areas for the ants and associated biodiversity in agro-ecosystems. This fact reinforces the need to preserve the Legal Reserves as described in Brazilian law.

Quantifying restoration success via natural recovery in forested areas following pipeline construction

Natural recovery is a restoration technique that relies on natural ecological processes to reestablish native ecosystems. This “minimal intervention” approach is typically more cost‐effective, less labor intensive, and can result in more diverse communities than more intensive restoration techniques. The purpose of this study was to determine if boreal forest vegetation can reestablish naturally after pipeline construction, and whether a site can be identified as similar to adjacent undisturbed areas within 10 years of pipeline construction. Four naturally recovered pipeline segments (1, 3, 5, and 10 years postreclamation) in west‐central Alberta were assessed. Plots were established on and off each pipeline segment right‐of‐way (ROW) in upland, transitional, and wetland habitats. Vegetation percent cover, vigor, and tree seedling density data were used to determine characteristic and indicator species, regulated weeds and agronomic species, richness, diversity, evenness, and tree establishment for each pipeline segment, habitat type, and site type (on‐ vs. off‐ROW). Threshold values for species richness and community diversity were determined using data collected from sites off‐ROW. Sites which fell within established thresholds were identified as on a trajectory toward restoration within 10 years postconstruction. Metrics for the older pipeline segments, including species richness, diversity, evenness, and seedling count were typically closer to threshold values, and sometimes exceeded them. Only the youngest pipeline segment had tree establishment values below calculated thresholds. This study is the first to provide empirical evidence and a method for identifying successful restoration trajectories for natural recovery of pipeline ROWs in boreal forest.

Seasonal patterns of spectral diversity at leaf and canopy scales in the Cedar Creek prairie biodiversity experiment

The relationship between biodiversity and spectral diversity is highly scale-dependent, and temporal variation in leaf morphological, biochemical traits and canopy structure can alter this relationship. However, the temporal dependence of the spectral diversity – biodiversity relationship is poorly understood, in part due to the difficulties of obtaining consistent measurements across space and time. Using leaf pigments and leaf and canopy reflectance throughout a growing season in the Cedar Creek prairie biodiversity experiment, we explored phenological effects on the scale dependence of the spectral biodiversity – biodiversity relationship. Leaf reflectance spectra displayed larger among-species variation than leaf pigments, indicating that leaf reflectance contained more information for distinguishing species than some leaf trait measurements. At the canopy scale, spectral variation derived using reflectance was mainly driven by among-species variation. The canopy scale spectral diversity was also influenced by changing vegetation percent cover, key phenological events (e.g., flowering), and disturbance (drought). Our results revealed that contrasting phenological patterns of spectral diversity metrics emerged at leaf and canopy scales. Because a misunderstanding of these contrasting temporal effects across spatial scales can lead to possible misinterpretations of the spectral diversity – biodiversity relationship or of their underlying causes, more research effort is needed to understand these cross-scale temporal effects.

Investigating the Ability to Identify New Constructions in Urban Areas Using Images from Unmanned Aerial Vehicles, Google Earth, and Sentinel-2

One of the main problems in developing countries is unplanned urban growth and land use change. Timely identification of new constructions can be a good solution to mitigate some environmental and social problems. This study examined the possibility of identifying new constructions in urban areas using images from unmanned aerial vehicles (UAV), Google Earth and Sentinel-2. The accuracy of the land cover map obtained using these images was investigated using pixel-based processing methods (maximum likelihood, minimum distance, Mahalanobis, spectral angle mapping (SAM)) and object-based methods (Bayes, support vector machine (SVM), K-nearest-neighbor (KNN), decision tree, random forest). The use of DSM to increase the accuracy of classification of UAV images and the use of NDVI to identify vegetation in Sentinel-2 images were also investigated. The object-based KNN method was found to have the greatest accuracy in classifying UAV images (kappa coefficient = 0.93), and the use of DSM increased the classification accuracy by 4%. Evaluations of the accuracy of Google Earth images showed that KNN was also the best method for preparing a land cover map using these images (kappa coefficient = 0.83). The KNN and SVM methods showed the highest accuracy in preparing land cover maps using Sentinel-2 images (kappa coefficient = 0.87 and 0.85, respectively). The accuracy of classification was not increased when using NDVI due to the small percentage of vegetation cover in the study area. On examining the advantages and disadvantages of the different methods, a novel method for identifying new rural constructions was devised. This method uses only one UAV imaging per year to determine the exact position of urban areas with no constructions and then examines spectral changes in related Sentinel-2 pixels that might indicate new constructions in these areas. On-site observations confirmed the accuracy of this method.

Factors contributing to the biodiversity value of an archaeological landscape in Jordan

Archeological landscapes are important places because they protect areas of historical importance, shape cultural and national identity, are recreational spaces, and vital sources of tourism revenue. Archaeological landscapes have the potential to assist in reptile conservation. The objective of this study was to compare the diurnal reptile richness of an archaeological site to the reptile richness of a nature reserve (treatment control for biodiversity value) and a modern olive grove (treatment control for poor biodiversity value). Our results suggest that archaeological landscapes provide valuable reptile habitat, as our archaeological site supported similar reptile richness as the natural site, with both sites having higher species richness than the modern olive tree farm. The high reptile richness and densities were the result of high potential food availability and habitat mosaic of relatively low tree density and open areas with exposed, tall, rocky ruins. Reptile richness had a negative relationship with tree density. The ruins and high food availability of the archaeological site supported higher densities of saxaphilic lizard species as the density of these species increased as mean maximum rock height and percentage of green ground vegetation cover increased. Promoting the reptile richness of archaeological sites provides another justification for the protection and visitor appreciation for archaeological sites as places of historical, cultural and biodiversity importance. Keywords: Stellagama stellio, Ptyodactylus puiseuxi, reptile richness, rock outcroppings, vegetation greenness indices

Confort térmico producido por la vegetación arbórea en el macrocentro de Bahía Blanca (Argentina)

Urban trees are essential since they generate multiple benefits to society, one of them is the mitigation of the urban heat island. The present work aims to obtain the thermal comfort produced by the arboreal vegetation in the downtown area of Bahía Blanca city. For this, Local Climate Zone of the study area was determined according to its characteristics and the percentage of vegetation cover was obtained using the online software I-tree Canopy. A survey of the street trees was also conducted to determine the most representative species. During the summer of 2020, measurements of air temperature and relative humidity were made under the canopy of fifteen trees, at 3:00 p.m., in 15 days typical of this thermal season. Then, by applying the vegetation comfort index, it was found that all the selected trees contribute to improve the thermal comfort of the population. However, there were differences among them, with Platanus acerifolia and Parasenegalia visco standing out for their higher magnitude and their impact on the decrease in air temperature under their canopies. In addition, problems related to street trees were identified and described, and finally proposals were established. These results allow to consider that, given the importance of trees in the urban microclimate, their coverage should be increased in the downtown area in order to contribute to thermal regulation during the summer. The need for regular maintenance work to avoid the problems detected in the roadside trees and to enhance the ecosystem services they provide was confirmed.

What are the factors influencing recreational visits to national forest parks in China? Experiments using crowdsourced geospatial data

Quantifying recreational visits to national forest parks (NFPs) and deciphering associating driving factors is significant for NFP protection, management, development, and planning; however, previous studies have primarily conducted questionnaire-based surveys or semi-structured individual interviews to gather limited data, while few have employed big data to effectively and efficiently estimate NFP visits and further explored correlated factors. This study used location-based service data from social media to quantify recreational NFP visits, and search for any associations with spatio-physical park factors selected based on previous constructive studies and NFP visitor perceptions of travel experiences posted on social media. A spatial error model with maximum likelihood estimation (SEM-MLE) was applied to investigate the significance. Sixty-eight (68) NFPs located in the Yangtze River Delta urban agglomeration (YRDUA) were selected as experimental cases. The results indicated that: (i) The number of NFP check-in visits was unevenly distributed across the YRDUA; (ii) NFP size and biodiversity (i.e., the number of vegetation and animal species) were not correlated with check-ins; (iii) Three NFP attributes (entrance fee, percent vegetation cover, and the presence of recreational water activities), one accessibility variable (potential visitors to NFP), and one transport variable (driving time to train station), had a significant influence on NFP check-ins, collectively explaining 49.69% of the observed variation. These findings can help NFP managers and planners understand the internal and external factors influencing recreational visits, thus more strategically informing nature-based tourism design and promotion campaigns.