Land cover (LC) maps are crucial to environmental modeling and define sustainable management and planning policies. The development of a land cover mapping continuous service according to the new ...EAGLE legend criteria has become of great interest to the public sector. In this work, a tentative approach to map land cover overcoming remote sensing (RS) limitations in the mountains according to the newest EAGLE guidelines was proposed. In order to reach this goal, the methodology has been developed in Aosta Valley, NW of Italy, due to its higher degree of geomorphological complexity. Copernicus Sentinel-1 and 2 data were adopted, exploiting the maximum potentialities and limits of both, and processed in Google Earth Engine and SNAP. Due to SAR geometrical distortions, these data were used only to refine the mapping of urban and water surfaces, while for other classes, composite and timeseries filtered and regularized stack from Sentinel-2 were used. GNSS ground truth data were adopted, with training and validation sets. Results showed that K-Nearest-Neighbor and Minimum Distance classification permit maximizing the accuracy and reducing errors. Therefore, a mixed hierarchical approach seems to be the best solution to create LC in mountain areas and strengthen local environmental modeling concerning land cover mapping.
This study presents vegetation land cover mapping based on Remote Sensing (RS) data processing, including satellite imagery scenes from Sentinel-2A, ASTER, and Landsat, in order to show the ...spatio-temporal correlation between the climate and environmental setting in Morocco. The main objective of this study is to contribute on land use planning and ecosystem protection. The distribution of vegetation in the study area was analyzed based on the satellite image processing and computing Normalized Difference Vegetation Index (NDVI). The study was conducted on different satellite imagery (Sentinel-2A, ASTER and the Landsat TM5, ETM+, and OLI) using SAGA GIS and SNAP software, to achieve two specific objectives: (1) conducting a comparative analysis of the NDVI calculation results from three satellite images (i.e., sentinel-2A, ASTER, Landsat 8); (2) highlighting the dynamics of the NDVI index from 1984 to 2020 by processing 35 satellite images from Landsat data Archive using SAGA GIS software, and then correlating these changes with other vegetation indices for the Marrakech-Haouz region provided by NOAA, namely: Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and NDVI indices. This study shows a repetitive fluctuation in the decrease of NDVI mean value from 1984 to 2020, due to the contrasting climate setting of the study area and the influence of the alternation of humid and dry periods in the High Atlas of Marrakech. In addition, the presented results underline that open-source software, such as SAGA GIS and SNAP can provide satisfactory results for vegetation coverage dynamics.
High Atlas; Marrakech; NDVI; SAGA GIS; SNAP; Satellite imagery.
Fertilization is one of the most important components of precision agriculture, ensuring high and stable crop yields. The process of spatial interpolation of soil sample data is recognized as a ...reliable method of determining the prescription rates for precise fertilization. However, the application of a free open-source geographic information system (GIS) software was often overlooked in the process. In this study, a method of precise fertilization prescription map creation was developed using an open-source GIS software to enable a wider and cheaper availability of its application. The study area covered three independent locations in Osijek-Baranja County. A method was developed for the fertilization of sugar beet with phosphorous pentoxide, but its application is universal with regard to the crop type. An ordinary kriging was determined as an optimal interpolation method for spatial interpolation, with the mean RMSE of 1.8754 and R2of 0.6955. By comparing the precision fertilization prescription rates to a conventional approach, the differences of 4.1 kg ha-1 for Location 1, 15.8 kg ha-1 for Location 2, and 11.2 kg ha-1 for Location 3 were observed. These values indicate a general deficit in soil phosphorous pentoxide, and precise fertilization could ensure its optimal content in the future sowing seasons.
Landslides are massive natural disasters all around the world. In general, our society is only concerned with the landslides that can cause economic distress and impact human life. Landslides in ...remote areas such as mountainous forests have often been neglected. Referring to the historical disaster event, forest landslides have vast potential to cause unexpected ecological and social damage. This study reveals the terrain characteristics of the complex mountainous forest area of Cameron Highlands (CH), Malaysia, and demonstrates an approach to evaluate the terrain sensitivity of CH. Terrain assessment can be a powerful tool to prevent or reduce the risk of landslides. In this study, terrain features; elevation, slope gradient, aspect, topography wetness index (TWI), and length-slope factor (LS Factor) were extracted using a Digital Terrain Model (DTM) at 10 m resolution. The selected terrain features were incorporated using weighted overlay analysis to derive a terrain sensitivity map (TSM) using SAGA GIS software. The map identified five types of terrain sensitivity classified as very high sensitivity, high sensitivity, moderate sensitivity, low sensitivity, and very low sensitivity; these areas have a coverage of 0.78 km2, 114.31 km2, 107.50 km2, 102.99 km2, and 0.65 km2, respectively. The findings suggest that the sensitive areas are scattered throughout all of the mountainous forests of CH; thus, this enhanced the risk of landslide. Results showed 79.25% accuracy, which is satisfactory to be a guideline for forest management planning and assist decision making in the respective region.
Earth Observation services guarantee continuous land cover mapping and are becoming of great interest worldwide. The Google Earth Engine Dynamic World represents a planetary example. This work aims ...to develop a land cover mapping service in geomorphological complex areas in the Aosta Valley in NW Italy, according to the newest European EAGLE legend starting in the year 2020. Sentinel-2 data were processed in the Google Earth Engine, particularly the summer yearly median composite for each band and their standard deviation with multispectral indexes, which were used to perform a k-nearest neighbor classification. To better map some classes, a minimum distance classification involving NDVI and NDRE yearly filtered and regularized stacks were computed to map the agronomical classes. Furthermore, SAR Sentinel-1 SLC data were processed in the SNAP to map urban and water surfaces to improve optical classification. Additionally, deep learning and GIS updated datasets involving urban components were adopted beginning with an aerial orthophoto. GNSS ground truth data were used to define the training and the validation sets. In order to test the effectiveness of the implemented service and its methodology, the overall accuracy was compared to other approaches. A mixed hierarchical approach represented the best solution to effectively map geomorphological complex areas to overcome the remote sensing limitations. In conclusion, this service may help in the implementation of European and local policies concerning land cover surveys both at high spatial and temporal resolutions, empowering the technological transfer in alpine realities.
This paper presents different approaches to map bark beetle infested forests in Croatia. Bark beetle infestation presents threat to forest ecosystems. Due to large unapproachable area, it also ...presents difficulties in mapping infested areas. This paper analyses available machine learning options in open-source software QGIS and SAGA GIS. All options are performed on Copernicus data, Sentinel 2 satellite imagery. Machine learning and classification options are maximum likelihood classifier, minimum distance, artificial neural network, decision tree, K Nearest Neighbor, random forest, support vector machine, spectral angle mapper and Normal Bayes. Kappa values respectively are: 0.71; 0.72; 0.81; 0.68; 0.69; 0.75; 0.26; 0.60; 0.41 which shows highest classification accuracy for artificial neural networks method and lowest for support vector machine accuracy.
Soil erosion is a global environmental challenge that the United Nations Sustainable Development Goal (UN SDG) #15 wants to address, and the topographic factor, according to the RUSLE (Revised ...Universal Soil Loss Equation) model, is one of the most critical factors causing soil erosion. In this study, we employed three separate digital elevation models of Taiwan, with horizontal resolution ranging from 20 to 90 m, to compute the LS factors based on the upslope contributing areas and multiple flow directions, utilizing the methodologies used by the European Soil Data Centre. This is the first study to create a map of Taiwan’s island-wide LS factors without using a fixed slope length of 40 m. To compare European Union countries with Taiwan, we also calculated their LS means, standard deviations, and coefficients of variation of LS factors. As a result, Taiwan’s high LS values are readily noticeable as compared to the EU. Taiwan’s LS factor is greater than that of any EU country and the United Kingdom, at 2.69 times the EU average. To put it another way, while all other erosive factors are held equal, Taiwan’s average soil erosion is about 2.69 times that of the EU. With an LS factor of 6.95, Austria has the highest average LS in the EU, yet it is 91 percent of Taiwan’s. The findings demonstrate that Taiwan has a far higher mean LS factor than any EU country or the United Kingdom, which helps to partially explain why soil erosion in Taiwan is substantially higher than in the EU.
Geographically isolated insular species face energetic restrictions and commonly evolve adaptations that distinguish them from their mainland ancestors. During the Pleistocene, several Mediterranean ...islands were inhabited by now extinct Hippopotamidae. They underwent diverse changes in locomotion, dentition and body size. Based on these differences, it is supposed that they occupied different ecological niches depending on their respective faunal complexes and available resources. In this paper, we assess the paleoecology of dwarfed hippopotami from Crete, Malta, Sicily and Cyprus using a novel dental multiproxy approach. We applied dental topography analysis (SAGA-GIS) to measure the mean slope of the dental occlusal surface, mirroring dietary adaptations, as well as 3D surface texture analysis (3DST) to quantify the surface of occlusal wear facets, which correlate with dietary abrasiveness. Low slope values were found in the larger, more hypsodont hippopotami, whilst the smaller Phanourios minor displayed the highest occlusal relief with large compression basins. Since Hippopotamus pentlandi exhibited lower mean slope values than the larger, more hypsodont Hippopotamus amphibius, we conclude that lower occlusal reliefs reflect adaptations to lower diet quality and arid environments, which are characteristic of freshwater-limited island habitats. The 3DST analysis revealed distinct ecological niches for the investigated insular hippos. Hippopotamus creutzburgi exhibited enamel surface textures analogous to those of Hippopotamus amphibius, a fresh grass grazer, thus confirming a semiaquatic lifestyle at the upland lake at Katharo, Crete. Hippopotamus pentlandi was bound to a similar niche to the extant form, probably due to the mainland character of its fauna, but experienced more dust intake. Hippopotamus melitensis had to cope with high ingestion of abrasives, seemingly on account of a more generalistic diet in its resource-limited and small habitat. Results point to either Phanourios minor broadening its dietary niche in its almost competition-free habitat, or suggest a dietary shift following a climatic change. The adopted multiproxy approach proved to be useful in identifying dental adaptations and individual foraging strategies linked to energetically restricted habitats, and therefore contributes to a better understanding of basic evolutionary and ecological principles.
•Novel multiproxy approach reveals dietary traits in Pleistocene dwarf hippopotami.•SAGA-GIS reveals dental adaptations, 3DST analysis individual forage behaviour.•Now extinct dwarfed island hippopotami occupied distinct ecological niches.•Lower occlusal reliefs evolved in dwarfed Hippopotamidae facing limited resources.•3DST analysis reveals specialisation, generalism or shifts in diet of dwarfed hippos.
The article presents the technique of landscape ecological modeling of water balance for the Southeast of Western Siberia. This technique enables to assess the impact of different types of land use ...on the structure of the water balance. For all elements of the landscape that make up the catchment area, i.e. surface complexes, characterized by their physical and geographical conditions, the main of them are the following: climate, topography, soil and vegetation. The combination of these conditions determines the features of structure of the water balance and hydrological regime of the territory. Knowledge of the structure of the water balance gives us an idea of the possibilities of using water resources of different geographical zones. In modelling we used the genetic method of flow formation, or the method of hydrological-climatic calculations (HCC) developed by V. S. Mezentsev implemented on the basis of landscape-hydrological approach in public geographic information system (GIS). The initial data for modeling are the following: digital terrain model, satellite sensing data and climatic characteristics. The system of equations of the HCC method describes the processes of formation of local climatic elementary runoff, changes in soil moisture and evaporation from the surface of catchments with the accuracy, which is sufficient for many practical purposes. In this method, the physical and geographical factors of flow formation are taken into account by the parameter n (reflects the influence of landscape conditions) and r (characterizes the ability of the soil to supply moisture to the evaporating surface and spend it on evaporation).
Particularly the Liguria region in Northern Italy is highly affected by soil erosion processes. This study was conducted in the Portofino promontory in eastern Liguria, to predict potential annual ...soil loss using the Revised Universal Soil Loss Equation (RUSLE). Moreover, we evaluate the relative accuracy of the predictions at detailed scale, using high resolution spatial information for model calibration. The RUSLE factors were calculated for the study area based on terrain survey data and rain gauge measurements. The results were plotted on a 1:10,000 scale soil erosion map and subsequently compared with the European soil loss estimation method (RUSLE2015) developed by the European Joined Research Centre. This study shows that the RUSLE2015 model can be applied in a typical Mediterranean environment such as the Portofino promontory. However, the accuracy of the single factors we calculated using high resolution data sets might improve the results substantially and thus, also model efficiency.
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