Google EarthTM Research Articles

The morphodynamics and sedimentology of a seasonally controlled microtidal tidal inlet: the Nariva River tidal inlet, Cocos Bay, Trinidad

Abstract The geomorphology and sedimentology of the Nariva River tidal-inlet complex, a microtidal fluvially influenced tidal-inlet complex, was analyzed. The complex comprises a recurved spit, an ebb-tidal channel, and an ebb-tidal delta. Morphological trends in the spatio-temporal evolution of the inlet complex were observed and recorded from Google Earth™ timelapse satellite images taken from 2003 to 2019. The two-dimensional internal architecture of the inlet complex and the sedimentary succession of the recurved spit, an ebb spit, the swash platform (of the ebb-tidal delta), a mouth bar (associated with the wet-season river-dominated inlet complex erosion), the ebb-tidal channel, and the adjacent foreshore were observed and documented from six shallow sedimentary cores. The Nariva River inlet width ranges from 17 to 40 m through its seasonal evolution, has a tidal prism of ∼ 2.17 × 105 m3, a cross-sectional area of 29.52 m2, and a depth ∼ 1.4 m (calculated at peak dry season near the inlet throat). The inlet complex undergoes an annual geomorphological evolution linked to the seasonally induced migration of the fluvial-to-marine transition zone (FMTZ). Increased fluvial discharge during the wet and hurricane seasons results in the basinward migration of the FMTZ rendering the inlet river dominated and resulting in the erosion of the inlet complex. During the dry season, low fluvial discharge, tidal dominance, and fair-weather conditions promote sedimentation in the inlet and the redevelopment of the inlet complex. The inlet has a complex (CX) internal architecture (fill pattern) defined by the laterally migrating recurved spit and ebb spit on their updrift margin, and conformable, mounded elements on their downdrift (e.g., mouth bar, swash platform, and foreshore). Two sedimentary successions were developed for ebb-tidal-delta deposits: off-axis of the ebb-tidal channel and on-axis. The off-axis succession is considerably similar to the adjacent foreshore-to-shoreface succession which can pose a challenge when attempting to identify these deposits in the rock record. The on-axis succession, however, despite thickness variability, showed a positive correlation to studied mesotidal tide-dominated inlet successions.

First evidence of widespread, severe soil erosion underneath centre-pivot irrigation systems

Centre-pivot systems are widely used for irrigation in agriculture. However, excessive water application rates under low pressure centre-pivot systems can lead to soil erosion, which degrades soil structure and increases crop vulnerability to droughts. Although efforts have been deployed to measure soil erosion underneath individual centre pivots, a large-scale systematic assessment of extent and severity of soil erosion in centre-pivot irrigated fields is currently lacking. Here we used Google Earth™ satellite images to provide first evidence of widespread, severe soil erosion in centre-pivot irrigated agricultural land. We focused on the municipality of Cristalina (6154 km2), in the Brazilian Central Highlands, where centre pivots irrigate approximately 60,000 ha of cropland. The study area is in the Cerrado biome, which is one of the most important grain-producing regions in the world and Brazil's main centre-pivot irrigation area. By mapping erosion features under centre pivots, we found that 29 % of centre-pivot fields displayed signs of rill erosion, with individual rills up to a length of 1200 m. Most erosion features were identified during the dry season of the Brazilian Cerrado, which coincided with the period of greater satellite-image availability. Moreover, we found that compacted centre-pivot-wheel tracks often triggered rill incision and that eroding centre-pivot fields displayed higher slope gradients and were better connected to surface waters than the non-eroding fields. Ultimately, the frequent identification of severe erosion features in the centre-pivot fields during the dry season indicates that irrigation causes and/or aggravates soil erosion in Cristalina and likely in other parts of the Brazilian Cerrado. This first systematic evidence of widespread soil erosion underneath centre-pivot systems highlights that irrigation erosion is an important but neglected driver of land degradation, and that urgent action is required to protect affected soils for future generations.

Abstract P3-04-02: Population level access to diagnostic mammography and ultrasound guided breast biopsy in Nigeria: a geospatial analysis

Abstract Introduction: Breast cancer is the most common cause of cancer-related mortality among women in Nigeria. Physical proximity to a diagnostic center is an important component of access, which has direct implication on the cost and timeliness of diagnosis and treatment. Beyond diagnostic mammography, ultrasound (US)-guided biopsy is an essential tool in the diagnostic pathway for suspicious lesions of the breast and is recommended by the Whole Health Organization Breast Health Global Initiative for LMICs. Unfortunately, there is a dearth of data on the population level access to mammography and US-guided breast biopsy in Nigeria and little is known about the geospatial inequities in access that targeted programming or investment could potentially address. This study undertook a comprehensive evaluation of breast imaging and diagnostic services in Nigeria and using a previously validated geographic information system (GIS) model, evaluated geospatial access to diagnostic mammography and US-guided breast biopsy in Nigeria. Methods: A comprehensive list of public and private facilities offering diagnostic mammography and/or US-guided breast biopsy was compiled using publicly available facility data from the Nigerian Ministry of Health, a survey administered to members of the Breast Imaging Society of Nigeria (BISON) as well as key stakeholder interviews from each of the countries six geopolitical zones. A novel survey was delivered to BISON members to identify additional/new facilities not captured by the latest Nigerian Ministry of Health data. Facility location, administration (public vs. private) and duration of service delivery were elicited from respondents and paired with the Ministry of Health facility dataset. Data on provider training and volume were also captured in the survey. All facilities were geolocated using Google Earth™ (Google, Mountain View, CA). A previously described cost-distance model, that uses open-source population density data to 100m2 (GeoData Institute) and road network data (OpenStreetMap) was used to estimate population level travel time to the nearest diagnostic center. Any portion of a route that included travel over terrain without roads was assigned a walking speed of 5 kmh-1. Geospatial access was calculated for mammography and US-guided biopsy separately and as well as by geopolitical zone. This study was approved by the research ethics board at Obafemi Awolowo University. Results: In addition to publicly available data from the Ministry of Health, facility and practice data was obtained from 63 Nigerian Radiologists from across the country. In total, 124 centers were identified that offer diagnostic mammography, of which 78 (63%) are privately administered. Nine of the countries 36 states did not have a center offering this service. Across the country, 33 centers offer US-guided breast biopsy, of which the majority (72.7%) are public. At a population level, 83.1% of the population has access within 120 minutes of continuous one-way travel to a center with diagnostic mammogram or US. At 240 minutes of continuous one-way travel, which corresponds to a full day of travel round-trip, 80.8% of the population has access to US-guided breast biopsy. However, there are differences in access between geopolitical zones. Just 68.7% of the population in the North East geopolitical zone has access to US-guided biopsy within a day’s travel (i.e. 240 minutes one-way). The remaining five geopolitical zones have population level access to this service of ≥80%. Conclusions: This is the first comprehensive evaluation of breast cancer imaging and diagnostic services in Nigeria. Our results, demonstrate that the majority of the population in Nigeria has reasonable geospatial access to basic breast cancer imaging services. However, there are inequalities in access between states and geopolitical zones in the north and south of the country, which may have an impact on timely diagnosis and care. Citation Format: Adeleye Omisore, Elizabeth J. Sutton, Gavin Tansley, Rachael Adeyanju AKINOLA, Gregory Knapp. Population level access to diagnostic mammography and ultrasound guided breast biopsy in Nigeria: a geospatial analysis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-04-02.

Geomorphology of a recently deglaciated high mountain area in Eastern Anatolia (Turkey)

ABSTRACT We present a geomorphological map of the Cilo Mountain range located in southeast Turkey that illustrates the recent evolution of the second-most glacierized area of Turkey. The map was produced by the manual delineating of landforms from highresolution satellite imagery (Pleiades and Google EarthTM images). Cilo Mountain glaciation played a crucial role in the evolution of the local physical landscape and even today glaciers are significant features. After the termination of Little Ice Age, deglaciation promoted the onset of multiple and intense surface processes; widespread slope instabilities, due to permafrost melting and frost weathering processes, are still the most active processes. Such processes are further promoted by the scarcity of vegetation. The occurrence of several proglacial lakes significantly contributes to the reduction of sediment output from glaciated watersheds, influencing the evolution of proglacial plains and resulting in a variety of landforms that we identified and described in this work.

Distribution and characteristics of Pleistocene ground thermal contraction polygons in Europe from satellite images

AbstractThe study of Pleistocene polygons in Europe carried out using the collection of satellite images available in Google Earth™ provides new data on the distribution of ground cracking by thermal contraction during glacial periods and sheds light on some factors controlling their formation. The distribution map shows that thermal contraction cracking affected terrain between latitude 43.5°N and the southern limit of the Fennoscandian Ice Sheet at 15 ka, with a concentration of polygons north of latitude 51°N. A clear asymmetry exists in relation to longitude, with a greater southward extension of polygons in France (43.5°N) than in central Europe (47°N). Analysis of the characteristics of polygons at the European scale reveals an association with lithology, latitude, and the age of the sediments in which they formed. The morphological evolution over time reconstructed from observations of polygons of contrasting ages indicates that a stable mature phase, characterized by small (mean size 15 m), regular polygons with numerous Y‐junctions, is reached after ca. 4 ka of thermal contraction cracking activity.

Spatial and seasonal analysis and geovisualization of Fasciola hepatica–free bovine bacillary hemoglobinuria outbreaks in eastern Uruguay, 1999–2019

Bovine bacillary hemoglobinuria (BBH) produced by Clostridium novyi type D, is an endemic, highly fatal disease of cattle in the temperate grassland region of eastern Uruguay. A previous study showed that in this region, BBH is not associated with Fasciola hepatica or any other known focal-ischemic liver injury, so the reasons for its high incidence remains undetermined. The objective of this study was to analyze data from 45 Fasciola hepatica-free BBH outbreaks (1999–2019) in order to find common animal, seasonal and/or geographical risk factors, which may explain the occurrence of the epizootics. Fisher’s goodness-of-fit testing showed a significantly higher case proportion of adult cows (N = 368, 80.5%) and lower of calves (N =8, 1.8%), as compared to the expected proportions of the censused population in the study area and historical submissions computed from the laboratory database (Chi-Sq = 346.2 and 174.8, df = 7, P < 0.00). Time series decomposition showed a bi-seasonal pattern, with a larger peak in spring and early summer (October to January) and a smaller increase in autumn (March-May). The lowest seasonal indices were on mid-summer (February) and winter (June-September). A combination of spatial statistics was used to assess the different spatial features of the disease and consistency of the findings. Global spatial autocorrelation showed BBH was significantly clustered (Moran’s I = 0.407, P < 0.001). Both smoothed Anselin’s Local Indicator of Spatial Autocorrelation and Kulldorff’s spatial scan Poisson and Bernoulli models, detected roughly the same high-risk areas in the southeastern part of the Merin Lagoon basin, with the most likely cluster centered in the large wetland biosphere reserve “Eastern Wetlands and Coastal Strip” (RR = 9.12, P < 0.001). Outbreaks were georeferenced (latitude, longitude) and thematic dot-mapping geovisualization in Google Earth™ showed that the results were robust and truly geographic in nature. Most outbreaks (40/45, 88.8%) occurred on wetlands areas and large river valleys, characterized by poorly drained and frequently flooded soils, indicating that moisture-laden soils are the natural habitat of C. novyi type D. Grasslands in these endemic areas support rapid fattening of cattle during spring-summer, and somewhat less in autumn, in almost exact correspondence with BBH peaks, suggesting a close causal association in high-risk areas. Risk is significantly higher in adult cows probably because the spore content in the liver is highest in this category. The altered lipid metabolism and lipotoxicity in the liver may be the precipitating factor for spore germination and epizootic occurrence.

Deriving the Main Cultivation Direction from Open Remote Sensing Data to Determine the Support Practice Measure Contouring

The P-factor for support practice of the Universal Soil Loss Equation (USLE) accounts for soil conservation measures and leads to a significant reduction in the modelled soil loss. However, in the practical application, the P-factor is the most neglected factor overall due to high effort for determining or lack of input data. This study provides a new method for automatic derivation of the main cultivation direction from seed rows and tramlines on agricultural land parcels using the Fast Line Detector (FLD) of the Open Computer Vision (OpenCV) package and open remote sensing data from Google Earth™. Comparison of the cultivation direction with the mean aspect for each land parcel allows the determination of a site-specific P-factor for the soil conservation measure contouring. After calibration of the FLD parameters, the success rate in a first application in the low mountain range Fischbach catchment, Germany, was 77.7% for 278 agricultural land parcels. The main reasons for unsuccessful detection were problems with headland detection, existing soil erosion, and widely varying albedo within the plots as well as individual outliers. The use of a corrected mask and enhanced parameterization offers promising improvements for a higher success rate of the FLD.

The qualitative and quantitative classification of modern clastic marginal-marine depositional systems, Trinidad

ABSTRACT Trinidad's modern coastal depositional systems are for the first time documented by (traditional) descriptive and (modern) semiquantitative and quantitative classification methods. The processes controlling the morphology and distribution of these systems are also investigated. Google Earth™ satellite images, together with published basinal processes data (e.g., significant wave height, surface littoral currents, and tidal cyclicity) are used to describe system morphology, map depositional elements, and to determine the processes responsible for system distribution, respectively. Coastal depositional systems along Trinidad's east, south, and west coasts comprise deltas, estuaries, tidal-inlet complexes, strandplains, and tidal flats. Their distribution is controlled by the wave regime, although they are also influenced by tidal and fluvial processes. The wave regime changes from wave-dominated along the open east coast, to mixed-energy wave-dominated along the semi-sheltered south coast, and to mixed-energy tide-dominated along the sheltered west coast. Distribution of depositional systems related to this regime are such that the wave-dominated east coast sees the development of wave-dominated estuaries. The south coast has a series of wave-dominated, tide- and river-influenced deltas. The sheltered west coast is the most morphologically diverse with river- and wave-dominated deltas, strandplains, and tidal flats. The application of semiquantitative and quantitative classification methods on modern systems has showed their competence in classifying mixed-influence systems from their morphology and sedimentary record. Quantitative classification using depositional elements lends an appreciation to the morphological signatures of mixed-influence systems. Quantitative classification for sedimentary sections gives an appreciation of the preservation of mixed-influence physical processes. The combination of both allows the correlation of the impact of physical properties on morphology and sedimentary record (i.e., possible disparities between morphology and processes). The combination of semiquantitative and quantitative methods may also hold the key to unlocking the mixed-processes classification of depositional elements.

Mapping the Dynamics of Winter Wheat in the North China Plain from Dense Landsat Time Series (1999 to 2019)

Monitoring spatio-temporal changes in winter wheat planting areas is of high importance for the evaluation of food security. This is particularly the case in China, having the world’s largest population and experiencing rapid urban expansion, concurrently, it puts high pressure on food demands and the availability of arable land. The relatively high spatial resolution of Landsat is required to resolve the historical mapping of smallholder wheat fields in China. However, accurate Landsat-based mapping of winter wheat planting dynamics over recent decades have not been conducted for China, or anywhere else globally. Based on all available Landsat TM/ETM+/OLI images (~28,826 tiles) using Google Earth Engine (GEE) cloud computing and a Random Forest machine-learning classifier, we analyzed spatio-temporal dynamics in winter wheat planting areas during 1999–2019 in the North China Plain (NCP). We applied a median value of 30-day sliding windows to fill in potential data gaps in the available Landsat images, and six EVI-based phenological features were then extracted to discriminate winter wheat from other land cover types. Reference data for training and validation were extracted from high-resolution imagery available via Google Earth™ online mapping service, Sentinel-2 and Landsat imagery. We ran a sensitivity analysis to derive the optimal training sample class ratio (β = 1.8) accounting for the unbalanced distribution of land-cover types. We mapped winter wheat planting areas for 1999–2019 with overall accuracies ranging from 82% to 99% and the user’s/producer’s accuracies of winter wheat range between 90% and 99%. We observed an overall increase in winter wheat planting areas of 1.42 × 106 ha in the NCP as compared to the year 2000, with a significant increase in the Shandong and Hebei provinces (p &lt; 0.05). This result contrasts the general discourse suggesting a decline in croplands (e.g., rapid urbanization) and climate change-induced unfavorable cropping conditions in the NCP. This suggests adjustments of the winter wheat planting area over time to satisfy wheat supply in relation to food security. This study highlights the application of Landsat images through GEE in documenting spatio-temporal dynamics of winter wheat planting areas for adequate management of cropping systems and assessing food security in China.

Geospatial analysis: a new frontier in humanitarian health research?

Geospatial analysis: a new frontier in humanitarian health research?

Using machine learning algorithm and landsat time series to identify establishment year of para rubber plantations: a case study in Thalang district, Phuket Island, Thailand

ABSTRACT In this study, we investigated the potential of using decision tree Machine Learning (ML) algorithm and profiles of vegetation and moisture indices extracted from Land Remote-Sensing Satellite (System, Landsat) time series to identify the ages of rubber plantations in Thalang district, Phuket province, southern Thailand. The secondary Land Use and Land Cover (LULC) data and historical imagery from Google EarthTM were used to distinguish plantation boundary and the establishment year of rubber plantation (T 0). The inter-annual profiles of spectral indices for each rubber plantation were obtained from 129 Landsat images (summer period from October 1991 to April 2018). The predictors were generated from summary distribution values of spectral indices during summer, including their difference and ratio at two years before to six years T 0 for Recursive Partitioning (RP) supervised classification algorithm. Modelling dataset from ‘known T 0’ plantations was divided into the training and testing datasets with a 60:40 ratio. The training model was 30 times repeated training while cross-validation assessment was tested to optimize an appropriated hyperparameter based on F 1 score. Then, the best performance training model was applied to both modelling and predicting (‘unknown T 0’ plantations) datasets. The predicted T 0 for each plantation was selected based on results aggregation of 100 times repeated prediction. The results show that the RP model with a complexity parameter as 0.01 and the predictors generated only from Normalized Difference Vegetation Index (NDVI) profile acceptable achieves an accuracy of 84.4% and 84.7% for lowland and highland modelling datasets, respectively. The root means squared error (RMSE) of predicted establishment year were 0.83 years at plantation scale.

Integrating C- and L-Band SAR Imagery for Detailed Flood Monitoring of Remote Vegetated Areas

Flood detection and monitoring is increasingly important, especially on remote areas such as African tropical river basins, where ground investigations are difficult. We present an experiment aimed at integrating multi-temporal and multi-source data from the Sentinel-1 and ALOS 2 synthetic aperture radar (SAR) sensors, operating in C band, VV polarization, and L band, HH and HV polarizations, respectively. Information from the globally available CORINE land cover dataset, derived over Africa from the Proba V satellite, and available publicly at the resolution of 100 m, is also exploited. Integrated multi-frequency, multi-temporal, and multi-polarizations analysis allows highlighting different drying dynamics for floodwater over various land cover classes, such as herbaceous vegetation, wetlands, and forests. They also enable detection of different scattering mechanisms, such as double bounce interaction of vegetation stems and trunks with underlying floodwater, giving precious information about the distribution of flooded areas among the different ground cover types present on the site. The approach is validated through visual analysis from Google EarthTM imagery. This kind of integrated analysis, exploiting multi-source remote sensing to partially make up for the unavailability of reliable ground truth, is expected to assume increasing importance as constellations of satellites, observing the Earth in different electromagnetic radiation bands, will be available.

A novel pixel-based supervised hybrid approach for prediction of land cover from satellite imagery

Background/Objectives: To determine the land use/cover from satellite imagery using image enhancement, image processing, and supervised machine learning techniques. This land usage will help in land use policy development, disaster assessment, planning of urban infrastructure, forest and agriculture monitoring and conservation. Methods/Statistical analysis: A pixel-based supervised hybrid machine learning approach is used that combines parametric density estimation followed by a k-nearest neighbor (k-NN) classifier to predict whether a particular pixel belongs to a nucleated village or to a field, forest, river, or some other terrain from satellite images. Spatial and texture features derived from the images are used as features for the models. Free satellite images crawled from Google EarthTM are hand labeled to serve as the ground truth for training and testing Models. Models are evaluated using four-fold cross validation. Comparison with other related techniques is also presented. Findings: Our experiments suggest that instead of using pixel intensity values as features, the intensity values after edge detection give better prediction accuracy. The parametric density estimation for the two classes is better modeled as Rayleigh distribution than as a normal distribution. Smoothing further helps improve the accuracy of the models. Passing the prediction of the parametric density estimator classifier through k-NN further reduces the error by removing the salt-and-pepper effects. Effects of using different size and number of smoothing filters is also discussed. Additionally, different parameters for k-NN were also evaluated to find the best models. The model was successful in achieving a very high accuracy of more than 97% with a very small false positive rate. The results demonstrate the successful discrimination of land cover of towns and nucleated villages from the surrounding terrain. Novelty/Applications: A pixel-based hybrid approach is proposed to improve accuracy of land cover classification. The proposed features and image enhancement techniques also help improve the prediction significantly. Using the proposed technique, the covered area of nucleated villages/towns can be determined for assessing the growth of towns/villages, for better of planning of urban infrastructure and land use policy, for disaster assessment, and forest and agriculture monitoring and conservation. Keywords: Land cover classification; land usage classification; satellite image classification; nucleated village segmentation

Underlying conditions on the southern border between Colombia and Venezuela to face the COVID-19 pandemic

To size human migration on the southern border between Colombia and Venezuela (Guainía department), and characterize the social, access and health care conditions relevant to the COVID-19 pandemic. Mixed epidemiological and ethnographic study. Rate of Venezuelan migrants was calculated according to Migration Colombia data until December 31st, 2019, also effective access to medical care, and provision of health posts were calculated, with information from each Guainía health post collected from June 2017 to June 2019, through semi-structured interviews, participant observations, Google Earth™ and Wikiloc™. Stata™ was used to calculate and graph median times of effective access. Cultural dynamics and health care conditions were described by the field work information and a permanent documentary review. Guainía is the 23rd department, according to the total number of Venezuelans, but the fourth in Venezuelans density (14,4%). In the Guainía river, the median times to the real reference health institution were 8,7 hours in winter and 12,3 in summer, and complex cases require air referrals. In the Inírida river, the median times to the real reference health institution were 11,9 hours in winter and 16,1 in summer. Only 57% of the health posts had supplies for acute respiratory infections. Facing COVID-19 in south border territories, it is necessary to immediately strengthen medical and public health services to avoid high fatality rates.

Turkish glacier inventory and classification from high-resolution satellite data

In view of the rapid and accelerating glacier retreat observed worldwide, the creation of an updated glacier inventory is fundamental to understand the glacier changes. Here we present the Turkish glacier inventory based on recent high-resolution satellite images (Pleiades, Google Earth™ and SPOT images). Outlines are manually digitized in ArcMap software. We identified 51 glaciers covering 12.29 km2: more than 60% of the Turkish glacierized area is located on Mount Ararat where the ice cap and four small outlet glaciers cover 7.37 km2. Turkish glaciation is characterized by small glaciers or glacierets partly debris-covered: only three glaciers (Erinç, Izbırak and Ararat glaciers) are larger than 0.5 km2. To assess the evolution of glaciers, we have focused on Mount Ararat where we digitized outlines for 1990, 1994, 2000 and 2016: in 26 years considered the glacier shows a retreat of 2.99 km2, − 29% of the initial value, showing a reduction rate dramatically higher than the main glacierized mountain ranges of the world.

Spatial and temporal distribution patterns of Precambrian mafic dyke swarms in northern Mauritania (West African craton): analysis and results from remote-sensing interpretation, geographical information systems (GIS), Google Earth ™ images, and regional geology

We used remote sensing, geographical information systems, Google Earth™ images, and regional geology in order to (i) improve the mapping of linear structures and understand the chronology of different mafic dyke swarms in the Ahmeyim area that belongs to the Archean Tasiast-Tijirit Terrane of the Reguibat Shield, West African craton, NW Mauritania. The spatial and temporal distributions with the trends of the dyke swarms provide important information about geodynamics. The analysis of the mafic dyke swarms map and statistical data allow us to distinguish four mafic dyke swarm sets: a major swarm trending NE-SW to NNE-SSW (80%) and three minor swarms trending EW to ENE-WSW (9.33%), NW-SE to WNW-ESE (9.06%), and NS (1.3%). The major swarms extend over 35 km while the minor swarms do not exceed 13 km. The Google Earth™ images reveal relative ages through crossover relationships. The major NE-SW to NNE-SSW and the minor NS swarms are the oldest generations emplaced in the Ahemyim area. The NW-SE-oriented swarm dykes which are cutting the two former swarms are emplaced later. The minor E-W to WSW-ENE swarms are probably the youngest. A precise U-Pb baddeleyite age of 2733 ± 2 Ma has been obtained for the NNE-SSW Ahmeyim Great Dyke. This dyke is approximately 1500 m wide in some zone and extends for more than 150 km. The distinct mafic dyke swarms being identified in this study can potentially be linked with coeval magmatic events on other cratons around the globe to identify reconstructed LIPs and constrain continental reconstructions. (Less)

Landslide susceptibility zonation mapping using GIS-based frequency ratio model with multi-class spatial data-sets in the Adwa-Adigrat mountain chains, northern Ethiopia

Different organizations reported that natural hazards related disasters killed hundreds of people and damaged infrastructures estimated millions of dollars every year worldwide. The purpose of this research was to generate landslide susceptibility zonation (LSZ) map for the first time and understand the main landside conditioning factors in the Adwa-Adigrat mountain chain (about 2540 km2). At initial stage, landslide inventory map was prepared using classical fieldwork, stereo aerial photographic analysis and interpretations (API) and Google Earth™ (GE) image interpretations. A total of 546 landslides were identified, located and delineated. Rock fall was the dominant type of landslide (170), while rock slide was the smallest (only 28 rock slides). Nearly 7.6% of the total study area is found to be affected by past and active landslides. Five spatial data-sets or landslide conditioning factors: lithology, land use and land cover, distance from streams, distance from lineament/faults, slope aspect and slope angle maps were prepared and analyzed. Frequency ratio (FR) model was used to generate LSZ map. The generated LSZ map was classified into very low, low, moderate, high and very high susceptibility zones. The validation and verification of the LSZ map was carried out using the accuracy statistics approach and the area under the curve (AUC) methods. Both methods confirmed the reliability and good fit of the FR method for the present study area. It was observed that 73.8% of the past landslides fell in the high and very high susceptibility zones. In mountain chains, field studies for landslide inventory and LSZ mapping is important. The produced LSZ map can help to predict and mitigate landslide related damages and risks, and future land use planning.

Permanent preservation areas in Mantiqueira sierra: perspectives for regularization along watercourses

Brazilian Native Vegetation Protection Law (Law n. 12.651/2012) brought flexibility related to the sizing of Permanent Preservation Areas (PPAs) along watercourses when there was anthropogenic occupation before July 22, 2008 (consolidated rural area), which may vary according to the size of the property. To better understand the effects of this law, we analyzed land use and land occupation in PPAs along watercourses in a portion of Grande River drainage basin. Scenarios were also developed to compare the effects of the reduction of PPA limits, allowing us to discuss measures to avoid water quality deterioration. We obtained the drainage network and individualized the study area through images available in Google Earth TM, and we extracted information about land use and land occupation from a vector provided by the Laboratory of Studies and Projects in Forest Management from Federal University of Lavras. Recovery scenarios were estimated according to Article n. 61-A from the Native Vegetation Protection Law. There was a significant reduction of environmental liability compared to previous legislation. In the more restrictive scenario, there may be a 31% deficit in recovery areas, where watersheds with a strong presence of small rural properties will be the most affected. Although the reduction of recovery areas is characterized as a retrogression in the protection of native vegetation, complementary strategies could be implemented, such as economic incentive mechanisms.

Sand circles in stony landscapes of Namibia are caused by large Euphorbia shrubs

Thousands of nearly stone-free, sandy, circular patches that lack vegetation (sand circles) are found in stony landscapes (including desert pavement areas) of Namibia and adjacent northwestern South Africa. Their distribution is very similar to that of Euphorbia gregaria, E. gummifera and E. damarana. The aim of this study was to determine if these sand circles represent sites of former occupancy by shrubby euphorbia species in the stony landscapes. Extracts of the soil from within and between sand circles (matrix), as well as from beneath dead E. gregaria plants were compared to an extract of a living E. gregaria with 1H-NMR and PCA multivariate statistical analysis. The results clearly showed that compounds characteristic of E. gregaria were present inside the sand circles and soil collected from beneath the dead plants but were not in extracts from the matrix soil. Diameters of living aerial parts of E. gregaria plants and sand circles measured in Google Earth™ satellite imagery showed that the average diameter of the sand circles and euphorbias were not statistically different.The aerial parts of Euphorbia gregaria are very dense and accumulate wind-blown sand particles. The accumulated sand buries the original stony surface beneath the aerial parts. When the plants die, a nearly circular sandy patch remains in these otherwise rocky areas. Many dying euphorbias have been observed in these areas and the healthy population seems to be declining. Previous reports on declining numbers of quiver trees (Aloe dichotoma) in Namibia were linked to climate change and the same might apply to succulent euphorbias. Since the shrubby euphorbias leave a sandy circle ‘footprint’ in the stony landscapes after they die, these features could potentially be used to estimate former population sizes and distributions and serve as a possible indicator of climate change.

Установление опорного значения удельной активности цезия-137 на распахиваемых склонах в перигляциальной области бассейна Верхней Оки: применение спутниковых снимков, ГИС и агрохимических показателей почвы

The paper deals with the issues of determining the reference value of specific activity of cesium-137 of Chernobyl origin when applying the radiocesium method to assess the loss of gray forest soil in the areas of spread of the microrelief of paleocryogenic origin in the periglacial region of the upper Oka basin. Paleocryogenic microrelief is recognized in spring satellite imagery available on Google EarthTM. The necessity of choosing a reference plot for a specific field that differs in microrelief, exposure, and the nature of soil cultivation is substantiated. The authors analyze the data, which they obtained during the field research in 2016-2019, on three agricultural fields located on the arable slopes of the northern and southern exposure in the upper Oka basin within the Orel district of the Orel Region. Three experimental plots, selected in close proximity to one another, differed both in exposure and in the content of humus, labile phosphorus and radiocaesium in the arable layer. Layer-by-layer soil sampling at block elevations within the reference plots located on watershed surfaces, gamma-spectrometric and agrochemical analyzes of soil samples allowed us to draw a number of systematically important conclusions. The first is that the reference value of radiocaesium in the arable layer should be determined within block elevations on the watershed surface of the slope or on inter-valley micro-water divisions on the water-divide surface (if it is not possible to select a reference plot on the watershed surface). The second is that the dimensions of the reference plots are determined by the size of the block elevations (the sizes of blocks in the area under study are 10-20 m). The third is that the reference value of radiocaesium should be determined individually for each field that differs in exposure and in the nature of the soil treatment. In the experimental plot, the reference value of the specific activity of cesium-137 increases in the following order: a field located on the water-divide surface of the northern exposure slope, with a grain rotation, with regular fertilizing (130.5 Bq/kg) — a field located on the watershed surface of the eroded slope southern exposure (174.7 Bq/kg) — a field located on the water-divide surface of a less fertilized and less eroded slope of the northern exposure (180 Bq/kg). The results of the study show that the use of the radiocaesium method in periglacial areas requires testing a fundamentally new approach to its implementation: at the stage of determining the reference value of radiocaesium, it is necessary to take into account the polygonal-block structure of the watershed surfaces.