Land Cover Modification Research Articles

Urbanisation and land-cover change affect functional, but not compositional turnover of bird communities

AbstractLand-use and land-cover change strongly affect biodiversity patterns and are assumed to be growing threats in the future. Particularly increasing urbanisation may affect species turnover and functional composition of biological communities. This study aimed to assess the characteristics of land-cover change in a medium-sized urban municipality from 2011 to 2018, and the effects of urbanisation on avian species- and functional diversity. The study was performed in Trondheim (Norway), using local land-cover maps and GBIF bird species occurrence records. GLMMs were used to model species turnover as a function of urbanisation, and the probability of species appearance and disappearance based on urbanisation and species traits. The extent of bird species turnover within a municipality-wide 500 × 500m2 grid was not predicted by a changes in developed area, but the probability of disappearance and appearance of bird species varied with urbanisation and bird functional traits. Species associated with urban- or open areas showed a decreasing probability of disappearing and an increasing probability of appearing with increasing amount of developed area within grid cells. Similarly, granivorous species showed a decreasing probability of disappearing. Species feeding above ground-level showed positive responses to changes in land-cover. The probability of both appearance and disappearance, thus species turnover, increased with increasing longevity. Most functional groups respond negatively to increasing urbanisation, indicating a potential impoverishment of local avifauna with future land-cover modifications. Considering planned future land-cover changes within the municipality, the local avian communities are in danger of homogenisation. The recommendations for local management are to minimise conversion of vulnerable habitats, such as wetlands and woodlands, in particular if these are converted to developed area.

Detection and characterization of coastal tidal wetland change in the northeastern US using Landsat time series

Coastal tidal wetlands are highly altered ecosystems exposed to substantial risk due to widespread and frequent land-use change coupled with sea-level rise, leading to disrupted hydrologic and ecologic functions and ultimately, significant reduction in climate resiliency. Knowing where and when the changes have occurred, and the nature of those changes, is important for coastal communities and natural resource management. Large-scale mapping of coastal tidal wetland changes is extremely difficult due to their inherent dynamic nature. To bridge this gap, we developed an automated algorithm for DEtection and Characterization of cOastal tiDal wEtlands change (DECODE) using dense Landsat time series. DECODE consists of three elements, including spectral break detection, land cover classification and change characterization. DECODE assembles all available Landsat observations and introduces a water level regressor for each pixel to flag the spectral breaks and estimate harmonic time-series models for the divided temporal segments. Each temporal segment is classified (e.g., vegetated wetlands, open water, and others – including unvegetated areas and uplands) based on the phenological characteristics and the synthetic surface reflectance values calculated from the harmonic model coefficients, as well as a generic rule-based classification system. This harmonic model-based approach has the advantage of not needing the acquisition of satellite images at optimal conditions (i.e., low tide status) to avoid underestimating coastal vegetation caused by the tidal fluctuation. At the same time, DECODE can also characterize different kinds of changes including land cover change and condition change (i.e., land cover modification without conversion). We used DECODE to track status of coastal tidal wetlands in the northeastern United States from 1986 to 2020. The overall accuracy of land cover classification and change detection is approximately 95.8% and 99.8%, respectively. The vegetated wetlands and open water were mapped with user's accuracy of 94.6% and 99.0%, and producer's accuracy of 98.1% and 93.5%, respectively. The cover change and condition change were mapped with user's accuracy of 68.0% and 80.0%, and producer's accuracy of 80.5% and 97.1%, respectively. Approximately 3283 km2 of the coastal landscape within our study area in the northeastern United States changed at least once (12% of the study area), and condition changes were the dominant change type (84.3%). Vegetated coastal tidal wetland decreased consistently (~2.6 km2 per year) in the past 35 years, largely due to conversion to open water in the context of sea-level rise.

Linking catchment structural units (CSUs) with water quality: Implications for ambient monitoring network design and data interpretation

Climate induced changes in runoff regimes and ongoing anthropogenic modification of land use and land cover (LULC) are shifting ambient water quality signals worldwide. Modulation of these signals by the physical catchment structure over different scales adds complexity to interpreting and analyzing measured data. Further bias may be introduced where monitoring networks are not representative of the structure of catchments in a given region. Here, we present a new environmental regionalization method to assess the representativeness of water quality monitoring (WQM) networks and to identify key structural drivers linked to water quality signals. Unique numerical codes were generated at the pixel level to provide wall-to-wall coverage of key Catchment Structural Units (CSUs) based on LULC, surficial geology, wetlands and slope. CSU codes were generated for all tributary (AT) catchments >20 km2 in Southern Alberta (n = 289), Canada, to determine the representativeness of an existing WQM network (54 tributary catchments) and to assess the explanatory power of CSUs with respect to water quality signals. Cluster analysis (CA) and multi-dimensional scaling (MDS) on the percent area of CSUs in the AT catchments identified six primary structural clusters in Southern Alberta. A clear gradient in catchment structure was evident progressing downstream from the Rocky Mountain headwaters through the foothills and prairie/plains region. Montane and grassland regions were found to be potentially under-represented by the current WQM program whereas catchments dominated by agriculture were likely over-represented. The disproportionate impact of specific CSU combinations on water quality was illustrated where the CA and MDS analyses indicated that even small percentages of urban areas and badland type topography results in elevated concentrations of total recoverable metals, nutrients and major ions. The application of the CSU approach in Southern Alberta demonstrates its value as an alternative method to assess and/or redesign existing WQM networks and to link water quality data to the structural composition of catchments. The general availability of the required data to generate CSUs provides universal potential for the approach to help assess other WQM programs and to contextualize data records. Applying the CSU approach when developing new ambient WQM networks can also help reduce the potential of over-monitoring similarly structured catchments as well as ensuring that all structural classes are represented by the data being generated.

Вплив категорій землекористування на прогноз WRF та його точність

In this research analysis of possibilities and methods of correction or reclassification of land use and land cover data, obtained modeling effects of using more accurate land use and land cover data and estimations of improvements of surface meteorological parameters simulations by mesoscale numerical atmospheric prediction (NWP) model. For the Kyiv region area, it is shown that the default WRF land use and land cover datasets are not ideal and contain various types of inaccuracies. Thus, compared to USGS, MODIS IGBP is characterized by a better spatial resolution, more correctly describing the urban built-up territories, forest areas and the Dnipro riverbed, but MODIS IGBP does not display small settlements. Analysis of other researches had shown that most of the reviewed studies are based on the case study approach, namely on an analysis of a small number of specific simulations. The disadvantage of this approach is that the sample size from which conclusions can be drawn is insignificant, so it is useful to compare similar studies for the consistency of the obtained results. The most consistent conclusions regarding the simulation improvement by the land use and land cover modification in the WRF model are related to the parameters of air temperature and humidity. Thus, the usage of more accurate and up-to-date land use and land cover databases in WRF simulations made it possible to reduce bias of forecasts and improved the accuracy of minimum and maximum daily temperature forecasts. The most significant improvement in the performed forecasts concerns the night temperature. The second parameter that were most often able to predict better is relative humidity. Improvement of simulated wind parameters using another land use and land cover dataset in the WRF model may be possible in urban areas and near the coast, especially as improving description of breeze circulation by the model. Assessments regarding the possibility of improving WRF precipitation simulation by land use and land cover dataset modification are not definite, although some works have noted the influence of the heat island of urbanized areas on redistribution of precipitation. On the one hand, in most of the analyzed scientific works, land use and land cover changes did not allow to significantly improve precipitation forecasts using the WRF model. On the other hand, it can be assumed that the physical and geographical conditions of a simulation domain as well as available moisture in the atmosphere is playing a more significant role in precipitation modeling than land use and land cover.

Urbanization favors the proliferation of Aedesaegypti and Culexquinquefasciatus in urban areas of Miami-Dade County, Florida

Urbanization processes are increasing globally. Anthropogenic alterations in the environment have profound effects on biodiversity. Decreased biodiversity due to biotic homogenization processes as a consequence of urbanization often result in increased levels of mosquito vector species and vector-borne pathogen transmission. Understanding how anthropogenic alterations in the environment will affect the abundance, richness, and composition of vector mosquito species is crucial for the implementation of effective and targeted mosquito control strategies. We hypothesized that anthropogenic alterations in the environment are responsible for increasing the abundance of mosquito species that are adapted to urban environments such as Aedesaegypti and Culexquinquefasciatus. Therefore, our objective was to survey mosquito relative abundance, richness, and community composition in Miami-Dade County, Florida, in areas with different levels of urbanization. We selected 24 areas, 16 remote areas comprised of natural and rural areas, and 8 urban areas comprised of residential and touristic areas in Miami-Dade County, Florida. Mosquitoes were collected weekly in each area for 24 h for 5 consecutive weeks from August to October 2020 using BG-Sentinel traps baited with dry ice. A total of 36,645 mosquitoes were collected, from which 34,048 were collected in the remote areas and 2,597 in the urban areas. Our results show a clear and well-defined pattern of abundance, richness, and community composition according to anthropogenic modifications in land use and land cover. The more urbanized a given area the fewer species were found and those were primary vectors of arboviruses, Ae.aegypti and Cx.quinquefasciatus.

PERFORMANCE ASSESSMENT OF CLASSIFICATION ALGORITHMS FOR LANDUSE / LANDCOVER CHANGE USING SENTINEL 2 DATA – A CASE STUDY OF TIRUPPUR

Abstract. In the history of mankind, one of the vibrant geographical phenomena is urbanization. The urbanization process is characterized by the expansion of the city from the core to peripheral areas which includes economic development, social, political forces and population density. Very rapid urbanization in the highly populated country like India, which changes natural land cover into urban land use, which is unavoidable. However, the study region Tiruppur is known as the knitwear capital of India that induces urban development in the region which results in the modification of the natural land cover. For understating the interaction between the natural landscape and human activities, land use and land cover (LULC) is considered as the important indicator. Research on land-use and land cover changes using remote sensing technology has a long history to evident. The advancement in the Remote Sensing and GIS techniques provide the fine resolution of data sets to proceed. Sentinel-2B imagery was chosen for this study for two main reasons one is that compare to Landsat imagery it has a high spatial resolution of 10 m and its radiometry includes three vegetation red edge bands. These two characteristics make the Sentinel-2B data appealing for LULC mapping. Different types of classification algorithms have been used to perform land use and land cover mapping. The study aims to create land use and land cover classification by making a comparison between different algorithms in Tiruppur by using Sentinel-2B satellite imagery. The commonly known classification algorithms, K-means, IsoData, support vector machines (SVMs), and maximum likelihood (ML) classification are adopted for investigation. This is followed by the selection of training pixels from the remaining classes to perform and compare different supervised learning algorithms for the first- and second-level classification in terms of accuracy rates. Accuracy was assessed through metrics derived from an error matrix, but primarily overall accuracy and kappa coefficient was used in allocating algorithm hierarchy. Finally, after the comparison, the highly accurate algorithm was suggested for the mapping of urban areas. The highest overall accuracy and kappa coefficient was produced by support vector machine (SVM) is due to the algorithm’s relatively small number of complex decision boundaries. The results are helpful to understand the performance of the classification algorithm for the future studies.

Analysis of geographic centrality and genetic diversity in the declining grasshopper species Bryodemella tuberculata (Orthoptera: Oedipodinae)

Human-induced ecological and climatic changes have led to the decline and even local extinction of many formerly widely distributed temperate and cold-adapted species. Determining the exact causes of this decline remains difficult. Bryodemella tuberculata was a widely distributed orthopteran species before the mid-19th century. Since then, many European populations have suffered drastic declines and are now considered extinct or critically endangered. We used ecological niche modelling based on a large dataset of extant and extinct occurrence data to investigate whether poor climatic suitability in the periphery of its global range was a possible cause of the local extinction of the European populations of B. tuberculata. We also used population genetics based on the COI marker to estimate and compare the genetic diversity of extant populations. We found that Europe still provides highly suitable habitats close to the climatic optimum, contradicting the assumption of climate change as major driver of this decline. Instead, changes in land-cover and other anthropogenic modifications of the habitats at the local scale seem to be the major reasons for local extinctions. Genetic analysis suggests Central Asia as center of diversity with a stable population size, whereas the effective sizes of the remaining European populations are decreasing. We found European genetic lineages nested within Central Asian lineages, suggesting a Central Asian source distribution area. Our results suggest that the declining European populations represent relics of a formerly wider distribution, which was fragmented by changes in land-use. These relics are now threatened by limited connectivity and small effective population sizes. Specific conservation actions, such as the restoration of former or potential new habitats, and translocation of individuals from extant populations to these restored sites may help slow, stall, or even revert the extinction process.

Spatial Analysis of a Chesapeake Bay Sub-Watershed: How Land Use and Precipitation Patterns Impact Water Quality in the James River

Changes in land cover throughout the Chesapeake Bay watershed, accompanied by variability in climate patterns, can impact runoff and water quality. A study was conducted using the Soil and Water Assessment Tool (SWAT) for the James River watershed in Virginia, the southernmost tributary of the Chesapeake Bay, from 1986 to 2018, in order to evaluate factors that affect water quality in the river. This research focuses on statistical analysis of land use, precipitation, and water quality indicators. Land cover changes derived from satellite imagery and geographic information system (GIS) tools were compared with water quality parameters throughout that timeframe. Marked decreases in forest land cover were observed throughout the watershed, as well as increased residential development. Our findings suggest strong links between land cover modification, such as residential development, and degraded water quality indicators such as nitrogen, phosphorus, and sediment. In addition, we note direct improvements in water quality when forest land areas are preserved throughout the watershed.

RETRACTED ARTICLE: Spatiotemporal Geospatial Modeling for 3D City Based on Edge Computing Using Statistical Framework Linear Injection Model Based on Multi-data Source Fusion

In recent years, data on individual spatiotemporal levels have been increasingly available, especially due to the utilization of modern GPS tracking devices. Cloud pollution significantly restricts the potential use for geoscience applications of optical remote sensing images. This paper presents a spatial and time-based melting process for remote imaging using a model of linear injection and information for neighborhood with edge computing assistance. The detailed data have proven helpful for inferring a more precise degree of transmission than conventional methods. Nevertheless, a lack of statistically sound frames remains for modeling mechanistically for the underlying transmission process and this development is particularly important to provide an individual general predictive epidemic framework. In this paper, a New Statistical Framework Linear Injection Model Based on Multi-Data Source Fusion method is proposed to determine the transmission of cloud-free image and to enhance the noise robustness. To improve its noise strength further, the local neighborhood information is introduced for refining initial fused stage image and to obtain more accurate prediction results, derived simultaneously from resolution fine image and fused result. To improve the spectral cohesion of recovered and remaining areas, correction residual strategy based on the Poisson equation has been analyzed. The tests demonstrated that the methods proposed for cases with substantial land cover modifications can work very well; they have less biases and more reliable performance compared with several cutting-edge approaches. To sum up, our solution is a major technical improvement to the current cloud removal system and offers the possibility of handling scenes with substantial land coverage changes.

Rapid expansion of human impact on natural land in South America since 1985.

Across South America, the expansion of commodity land uses has underpinned substantial economic development at the expense of natural land cover and associated ecosystem services. Here, we show that such human impact on the continent's land surface, specifically land use conversion and natural land cover modification, expanded by 268 million hectares (Mha), or 60%, from 1985 to 2018. By 2018, 713 Mha, or 40%, of the South American landmass was impacted by human activity. Since 1985, the area of natural tree cover decreased by 16%, and pasture, cropland, and plantation land uses increased by 23, 160, and 288%, respectively. A substantial area of disturbed natural land cover, totaling 55 Mha, had no discernable land use, representing land that is degraded in terms of ecosystem function but not economically productive. These results illustrate the extent of ongoing human appropriation of natural ecosystems in South America, which intensifies threats to ecosystem-scale functions.

Impact of open pit coal mining on the forest landscape ecology using spatial metrics: a study of Barabani C.D. block, West Bengal

Mining is an extractive activity that creates pits, scars and waste dump especially when operated on open cast basis that not only degrades the landscape structure but also have significant impact over its functioning. There is a general consensus about the role of forest as an important entity of landscape structure in maintaining the ecological balance which is under immense pressure by the various anthropogenic activities like growth of built up area by means of urban industrial growth and expansion of mining area. This study has been conducted with an objective to assess the ecological health of the forest landscape and to analyse the land use land cover change in Barabini C.D. block of West Bengal, Eastern India where hectares of forest land has been greatly modified by open pit coal mining. The study has employed two satellite images of 2000 and 2017 to assess the land use land cover and spatial metrics of the study area. Modification of land use land cover to a large extent has been reported during the specified time, for instance, forest cover and agricultural land decreased considerably; built up area and mining area has been increased to a great extent. Landscape matrices of class level and landscape level concerning with the surface, shape, edge character and spatial distribution has been calculated to analyzed the spatio temporal character of the landscape. Increase in the landscape level spatial metrics value indicative of the development of a complex landscape structure with shrinking vegetative cover. The result of class level indices also reported that, the forest land not only fragmented by the formation of open cast pit but also experienced huge spatial loss over the specified time. This phenomenal change of the landscape structure is a matter of serious environmental concern that needs immediate attention for the sustainability of the region.

Land cover dynamics and their driving factors in a protected floodplain ecosystem

AbstractFloodplains are simultaneously the most productive and threatened ecosystems in the world, with land cover integrity compromised even in “protected” floodplains. Due to their rich biodiversity, monitoring of land cover and understanding the causative drivers becomes imperative in the protected floodplains. This work performs spatio‐temporal assessment of land cover changes and discovers the underlying processes in the largest protected floodplain of the Brahmaputra River (BR)—Kaziranga National Park (KNP). Remotely sensed images of 1988, 1998, 2008, and 2018 were analyzed using visual interpretation techniques coupled with class description keys in GIS platform along with ground‐based surveys. Results show a substantial area decline under Dense Forest (7.7%), Open Forest (10%), Waterlogged wetland (31.3%), and Marsh/Swamp (70.4%) land cover classes between 1988 and 2018. The considerable reduction in forests and wetlands is likely to impact the life support system of the park as they form the key habitats and food resources. Concurrently, dramatic area increase under riverine classes has led to huge landmass loss along the northern and eastern stretch. Though the BR and the local flood pulse are essential source of nutrient replenishment in the park, they also act as primary drivers of land cover alteration. Hydro‐geomorphic processes like bank erosion, high‐flood events, and siltation in association with vegetation succession and invasive species control the inter‐conversion of land cover classes in the KNP. The findings of this work provide an insight into the natural factors that instigate the land cover modification on large floodplains in general, and particularly in KNP.

Urban Expansion and Its Impact on the Livelihood of Peripheral Farming Communities: The Case of Assosa Town, Benishangul Gumuz Region, Ethiopia

Assosa town’s expansion program which had been experiencing a horizontal expansion starting from its historical expansion pattern currently implemented via expropriating peripheral land holders of earlier rural dwellers by solely decision of town administration and the investigation randomly targeted to per-urban areas from four peripheral kebeles surrounding of town. Therefore, the objective of this study is to assess Urban Expansion and its Impact on Peripheral Farming Communities: The Case of Assosa town, BGR, Ethiopia Thus the study investigated the impact of urban expansion on the peripheral community livelihood in case of Assosa town. Questionnaire, survey, focus group discussion and key informants interviews were tools of data collection from 160 sampled households living in sampled kebeles via systematic random sampling technique and judgmental technique for FGD and interview. The results of the study indicated that there is infrastructural improvement, socio economic growth, rapid population growth and also socio-economic problems related to urban expansion in studied area. There is great spatial and temporal land use land cover modification more towards to build up land uses. The livelihood condition of per-urban community changed to non-agricultural form but there are policy and strategy gaps of expropriating, compensating for affected community in ground implementation. Landholder expropriated should be recompensed for equal socio-economic beneficially from urbanization and further skill-oriented training for new livelihood strategy and also accessing credit and rehabilitating strategy were recommended for affected community livelihood.

Large‐scale land acquisition as a potential driver of slope instability

AbstractRecently, vast tracts of land have been acquired by foreign and domestic–foreign partnerships to satisfy an increasing demand for agricultural products, often resulting in the conversion of forested landscapes into agricultural fields. Those conversions often occur in areas characterized by high slope angles with the potential to cause mass wasting and shallow landslides. An interesting case‐study is the Licungo basin in Mozambique, where from 2000 nearly 160,000 ha of forest were converted, 17% of which occurred in areas acquired through large‐scale land acquisitions (LSLAs). This study analyses the relationship between deforestation occurring within LSLA areas and the likelihood of landslide occurrence. To this end, we use a spatially distributed physically based model that couples the assessment of slope stability with hillslope‐scale hydrological processes and evaluates the change in slope stability associated with remotely sensed forest loss. Relative to conditions where no human modification of land cover has occurred, we find that LSLAs have the potential to increase the extent of areas susceptible to slope failure by as much as 15,000 ha. We also quantified potential direct and indirect implications of such events for the food supply of local populations, estimating that 4,000 people could lose approximately 700 kcal cap−1 d−1 if all LSLAs are put under production. This study demonstrates the linkages between LSLAs, slope instability, and knock‐on environmental and societal impacts. Governments should therefore take such impacts into account (in addition to those related to habitat destruction and carbon emissions) when issuing permits and concessions within forested lands.

Structural changes of vegetation and its association with microclimate in a successional gradient of low thorn forest in northeastern Mexico

Understanding how microclimate and vegetation are associated during secondary succession is of primary importance for plant conservation in the face of the increasing land cover modification. However, these patterns are still unstudied for many plant communities. This study aimed to evaluate the structure (species richness, Shannon's diversity index, Simpson´s dominance index, abundance of each species, average height of species, species cover (%), species composition, and indicator values) of a low thorn forest fragment and to analyze its relation with microclimate along a successional gradient. Four stages of succession were delimited by the analysis of Landsat images, in the state of Tamaulipas, northeast Mexico. Statistical models incorporated species richness, diversity indices, abundance, height, and cover, as variables for searching differences between stages, or to evaluate microclimate associations. A total of 70 species, 54 genera, and 27 families were determined. Height of tree layer was the most important variable for discrimination of the successional stages. Conserved areas differed floristically from other stages, associated mainly with the lowest values of wind speed originated by tree layer characteristics. A significant association between species and microclimate was found, being wind speed and relative humidity the most important variables. Some species, due to their high importance values and their patterns of association with microclimate, may be considered as key taxa for low thorn forest, which is a threatened semitropical community in northeast Mexico. Conserved and late successional areas account for climatic regulation of this plant community, and the importance of these forest patches may be considered when establishing biodiversity protection areas.

Quadrennial variability and trends of surface ozone across China during 2015–2018: A regional approach

China has undergone headlong economic development, yielding a secondary air pollutant ‘ozone’, which has stirred up worldwide concerns. This study evaluates quadrennial, and seasonal surface ozone variations, ozone trends along with its significance through seasonal and deseasonal datasets, and ozone-NO2 correlation to codify a precedent for pollution control policies. China is divided into eight regions namely: Northeast (NE), Northwest (NW), North (N), East (E), Central (C), South (S), Southwest (SW), and Tibet (T), to exploit four-years data via (a) ozone 8-hr moving averages (O3-8hr), (b) hourly ozone monthly mean (O3-MM), (c) hourly ozone daily maximum MM (O3-DM-MM), (d) mean of the daily maximum 8-hr average ozone (MDA8-O3), (e) hourly ozone averages (O3-1hr), and (f) hourly NO2 averages (NO2-1hr), respectively. Quadrennial variations show distinct regions (i) Northeast with daily upraised value of 164.59 μg/m3, (ii) North possessing increased monthly variation of 125 μg/m3, and (iii) Tibet containing maximum yearly value of 79.81 μg/m3, respectively. Seasonal variations outpace North and South regions. The highest and lowest values of seasonal variations in North region are 135.61 μg/m3, and 23.96 μg/m3 during summer and winter, while maximum values of South region are 87.98 μg/m3 in autumn. In trend analysis, the seasonal dataset highlights higher ozone values during autumn, i.e. 74.12 μg/m3 and 141.96 μg/m3 for South and Central regions, respectively. In the meantime, the deseasonal dataset reveals the presence of increasing ozone trends in all studied regions. In assessing statistical significance by Mann-Kendall test, seasonal dataset rolls out statistically insignificant trends with an exception of South region. Meanwhile, deseasonal dataset projects statistically significant trends in all the eight regions. Lastly, two continual regions North and South are selected to determine ozone-NO2 relationship. The multiple analytical approaches unveil that O3 has increased by 20.86%, 14.05% and 12.64% in North, Central and South regions. The dissimilar climate, land cover modifications, precursors transportation and vehicular emissions might be some of the rationales to give rise to regional ozone variations. Therefore, we suggest revamping of emissions control policies and their precise implementation to abate ozone pollution.

Estimating Human Impacts on Soil Erosion Considering Different Hillslope Inclinations and Land Uses in the Coastal Region of Syria

Soils in the coastal region of Syria (CRoS) are one of the most fragile components of natural ecosystems. However, they are adversely affected by water erosion processes after extreme land cover modifications such as wildfires or intensive agricultural activities. The main goal of this research was to clarify the dynamic interaction between erosion processes and different ecosystem components (inclination, land cover/land use, and rainy storms) along with the vulnerable territory of the CRoS. Experiments were carried out in five different locations using a total of 15 erosion plots. Soil loss and runoff were quantified in each experimental plot, considering different inclinations and land uses (agricultural land (AG), burnt forest (BF), forest/control plot (F)). Observed runoff and soil loss varied greatly according to both inclination and land cover after 750 mm of rainfall (26 events). In the cultivated areas, the average soil water erosion ranged between 0.14 ± 0.07 and 0.74 ± 0.33 kg/m2; in the BF plots, mean soil erosion ranged between 0.03 ± 0.01 and 0.24 ± 0.10 kg/m2. The lowest amount of erosion was recorded in the F plots where the erosion ranged between 0.1 ± 0.001 and 0.07 ± 0.03 kg/m2. Interestingly, the General Linear Model revealed that all factors (i.e., inclination, rainfall and land use) had a significant (p < 0.001) effect on the soil loss. We concluded that human activities greatly influenced soil erosion rates, being higher in the AG lands, followed by BF and F. Therefore, the current study could be very useful to policymakers and planners for proposing immediate conservation or restoration plans in a less studied area which has been shown to be vulnerable to soil erosion processes.

A spaceborne SAR-based procedure to support the detection of landslides

Abstract. The increasing availability of free-access satellite data represents a relevant opportunity for the analysis and assessment of natural hazards. The systematic acquisition of spaceborne imagery allows for monitoring areas prone to geohydrological disasters, providing relevant information for risk evaluation and management. In cases of major landslide events, for example, spaceborne radar data can provide an effective solution for the detection of slope failures, even in cases with persistent cloud cover. The information about the extension and location of the landslide-affected areas may support decision-making processes during emergency responses. In this paper, we present an automatic procedure based on Sentinel-1 Synthetic Aperture Radar (SAR) images, aimed at facilitating the detection of landslides over wide areas. Specifically, the procedure evaluates changes of radar backscattered signals associated with land cover modifications that may be also caused by mass movements. After a one-time calibration of some parameters, the processing chain is able to automatically execute the download and preprocessing of images, the detection of SAR amplitude changes, and the identification of areas potentially affected by landslides, which are then displayed in a georeferenced map. This map should help decision makers and emergency managers to organize field investigations. The process of automatization is implemented with specific scripts running on a GNU/Linux operating system and exploiting modules of open-source software. We tested the processing chain, in back analysis, on an area of about 3000 km2 in central Papua New Guinea that was struck by a severe seismic sequence in February–March 2018. In the area, we simulated a periodic survey of about 7 months, from 12 November 2017 to 6 June 2018, downloading 36 Sentinel-1 images and performing 17 change detection analyses automatically. The procedure resulted in statistical and graphical evidence of widespread land cover changes that occurred just after the most severe seismic events. Most of the detected changes can be interpreted as mass movements triggered by the seismic shaking.

Influence of land-use/land-cover change on landscape connectivity for an endemic threatened amphibian (Argenteohyla siemersi pederseni, Anura: Hylidae)

Modifications in natural landcover generally result in a loss of habitat availability for wildlife and it’s persistence will depend largely on their spatial configuration and functional connections. Argenteohyla siemersi is a threatened and endemic amphibian whose habitat is composed of forest patches near rivers and water bodies edges. This study aimed to analyse the accessible habitat for this species and identify key elements to maintain its ecological network in two different types of land uses: an anthropized area with extensive cattle raising and a protected area. The structural and functional characteristics of both landscapes were analyzed. The connectivity at landscape level and the contribution of each habitat patch were evaluated through simulation models with different dispersion distances in the context of the graph theory. In both landscapes, nine types of landcover were identified with different compositions. Remarkable differences were found in habitat connectivity for this amphibian species between both landscapes. As the percentage of dispersion distance increases, reachable habitat increases as well, although with higher percentages in the protected area. Two corridors were identified in the protected landscape and one in the rangeland one; patches and key links constituted all of them. The present work provides spatially explicit results with a quantitative basis. It could be useful as a tool for the development of management plans aimed at guaranteeing the functionality of the ecological network for this endangered species and, therefore, contribute to its long-term conservation.

Surface runoff and soil erosion in a natural regeneration area of the Brazilian Cerrado

The Brazilian Cerrado has been converted to farmland, and there is little evidence that this expansion will decrease, mainly because agriculture is the country’s main economic sector. However, the impacts of intense modification of land use and land cover on surface runoff and soil erosion are still poorly understood in this region. Here, we assessed surface runoff and soil loss in a woodland Cerrado area under a former pasture area, which was abandoned and has undergone a natural regeneration process for 7 years (RC). Its results were compared with that found in an undisturbed area of woodland Cerrado (CE), 40-month-old eucalyptus (3.0 × 1.8 m) (EU), and pasture under rotational grazing (PA). The study was conducted on Red Acrisol located in the Brazilian Cerrado. We performed rainfall simulations on a plot of 0.7 m2 and using three constant rainfall intensities of 60, 90, and 120 mm h−1 for 1 h. For each rainfall intensity, we carried out four repetitions using different plots in each treatment, i.e. 12 plots per treatment studied and 48 plots in total. We noted that the soil physical properties were improved in RC and, consequently, water infiltration and soil erosion control; RC presented surface runoff and soil loss different from EU and PA (α = 0.05). The macroporosity and soil bulk density affected surface runoff in RC and PA because the RC was used as pasture and is currently regenerating back to the cerrado vegetation. As the rainfall intensity increased, EU became more similar to PA, which showed the highest surface runoff and soil loss. Our findings indicate that natural regeneration processes (pasture to the cerrado vegetation) tend to improve the soil ecosystem services, improving infiltration and reducing surface runoff and soil erosion.