We present a phenology-based approach for optimizing the number and timing of unmanned aerial vehicle imagery acquisition, based on a priori near-surface observations. A ground-placed camera was used for generating annual time series of spectral indices in four different East Mediterranean sites. The time series dataset represented 1852 individuals of 12 common vegetation species. Feature selection was used for identifying the optimal dates for species classification. A UAV was flown for acquiring five overhead multiband orthomosaics, based on the five optimal dates identified in the feature selection of the near-surface time series of the previous year. An object-based classification was used for species classification, and resulted in an average overall accuracy of 85% and an average Kappa coefficient of 0.82. This cost-effective approach has high potential for detailed vegetation mapping, regarding the accessibility of UAV-produced time series, compared to hyper-spectral imagery wi

Tracking global and regional conflict zones requires spatially explicit information in near real-time. Here, we examined the potential of remote sensing time-series data (night lights) and big data (data mining of news events and Flickr photos) for monitoring and understanding crisis development and refugee flows. We used the recent Arab Spring as a case study, and examined temporal trends in monthly time series of variables which we hypothesized to indicate conflict intensity, covering all Arab countries. Both Flickr photos and night-time lights proved as sensitive indicators for loss of economic and human capital, and news items from the Global Data on Events, Location and Tone (GDELT) project on fight events were positively correlated with actual deaths from conflicts. We propose that big data and remote sensing datasets have potential to provide disaggregated and timely data on conflicts where official statistics are lacking, offering an effective approach for monitoring geopolitical and environmental changes on Earth.

ABSTRACTThe economic and socio-political interactions between countries can have major impacts on transboundary conservation decisions and outcomes. Here, we examined for 14 Western Indian Ocean (WIO) continental and island nations the extent of their marine coral reef species, fisheries and marine protected areas (MPAs), in the context of their geopolitical and socio-economic connections. We also examined the role of external countries and organisations in collaboration within the region. We found large variation between the different countries in their protected area size, and management, which result from different interests in establishing the MPAs, ranging from fisheries management, biodiversity conservation to asserting sovereignty claims. Seventy-four per cent of the 154 MPAs in the region belong to island nations; however, the largest MPAs in the WIO were established by European powers, and include Mayotte and Glorioso Islands (France) and Chagos (UK). While the majority of MPAs are managed by individual countries, between-country collaboration within and outside the region is key if the aim is to achieve effective conservation of ecosystems and species across the island and mainland nations in the region. This may be advanced by creating transboundary MPAs and by regional conservation investment by external powers that benefit from the region’s resources.

* While marine environments are three-dimensional (3D) in nature, current approaches and tools for planning and prioritising actions in the ocean are predominantly two dimensional. Here, we develop a novel 3D marine spatial conservation prioritisation approach, which explicitly accounts for the inherent vertical heterogeneity of the ocean. This enables both vertical and horizontal spatial prioritisation to be performed simultaneously. To our knowledge, this is the first endeavour to develop prioritisation of conservation actions in 3D. * We applied the 3D spatial conservation prioritisation approach to the Mediterranean Sea as a case study. We first subdivided the Mediterranean Sea into 3D planning units by assigning them a z coordinate (representing depth). We further partitioned these 3D planning units vertically into three depth layers; this allowed us to quantify biodiversity (1,011 species and 19 geomorphic features) and the cost of conservation actions at different depths. We adapted the prioritisation software Marxan to identify 3D networks of sites where biodiversity conservation targets are achieved for the minimum cost. * Using the 3D approach presented here, we identified networks of sites where conservation targets for all biodiversity features were achieved. Importantly, these networks included areas of the ocean where only particular depth layers along the water column were identified as priorities for conservation. The 3D approach also proved to be more cost-efficient than the traditional 2D approach. Spatial priorities within the networks of sites selected were considerably different when comparing the 2D and 3D approaches. * Prioritising in 3D allows conservation and marine spatial planners to target specific threats to specific conservation features, at specific depths in the ocean. This provides a platform to further integrate systematic conservation planning into the wider ongoing and future marine spatial planning and ocean zoning processes.

The VIIRS-DNB sensor launched in 2011 offers the remote sensing community improved capabilities for monitoring and quantifying nighttime brightness. So far, most studies of temporal changes in nighttime lights were focused on examining inter-annual trends or on sudden changes in light emission, related to demographic and economic reasons. Here, the recently released two year (2014-2015) set of monthly cloud-free VIIRS-DNB composites was used to explicitly examine seasonal changes in nighttime lights and their correspondence with seasonality of land cover in Northern and Central America. It was found that monthly changes in nighttime brightness were positively correlated with monthly changes in snow cover and in albedo, and negatively correlated with monthly changes in NDVI. These correlations were strongest in urban areas in the northeast of the USA, where high correlation coefficient values (>0.8) were obtained. Seasonality in nighttime brightness is thus an important factor to consi

On-going changes in drought, vegetation and wildfires in Israel provide a key example of possible future evolution in transition areas at the border between Mediterranean and arid climates. Here we present multiple lines of evidence suggesting that drought conditions in Israel, representing the eastern Mediterranean, have increased during the period 1980–2014. Drought conditions were calculated using the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSI). A 30-year series (1982–2011) of monthly Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) indicates generally positive trends in winter and spring and negative ones in summer and autumn, except in the transition zone between the southern Negev desert and the Mediterranean climate region, where a statistically significant negative trend in all seasons was found. Available ground observations suggest that fire

Ecological bias may result from interactions between variables that are characterized by different spatial and temporal scales. Such an ecological bias, also known as aggregation bias or cross-level-bias, may occur as a result of using coarse environmental information about stressors together with fine (i.e., individual) information on health outcomes. This study examines the assumption that distinct within-area variability of spatial patterns of the risk metrics and confounders may result from artifacts of the aggregation of the underlying data layers, and that this may affect the statistical relationships between them. In particular, we demonstrate the importance of carefully linking information layers with distinct spatial resolutions and show that environmental epidemiology studies are prone to exposure misclassification as a result of statistically linking distinctly averaged spatial data (e.g., exposure metrics, confounders, health indices). Since area-level confounders and expo

Cumulative human impacts have led to the degradation of marine ecosystems and the decline of biodiversity in the European and contiguous seas. Effective conservation measures are urgently needed to reverse these trends. Conservation must entail societal choices, underpinned by human values and worldviews that differ between the countries bordering these seas. Social, economic and political heterogeneity adds to the challenge of balancing conservation with sustainable use of the seas. Comprehensive macro-regional coordination is needed to ensure effective conservation of marine ecosystems and biodiversity of this region. Under the European Union Horizon 2020 framework programme, the MarCons COST action aims to [...]

Parks and protected areas provide a wide range of benefits, but methods to evaluate their importance to society are often ad hoc and limited. In this study, the quality of crowdsourced information from Public Participation GIS (PPGIS) and Volunteered Geographic Information (VGI) sources (Flickr, OpenStreetMap (OSM), and Wikipedia) was compared with visitor counts that are presumed to reflect social importance. Using the state of Victoria, Australia as a case study, secondary crowdsourced VGI data, primary crowdsourced (PPGIS data) and visitor statistics were examined for their correspondence and differences, and to identify spatial patterns in park popularity. Data completeness – the percent of protected areas with data – varied between sources, being highest for OSM (90%), followed by Flickr (41%), PPGIS (24%), visitation counts (5%), and Wikipedia articles (4%). Statistically significant correlations were found between all five measures of popularity for protected areas. Using ste

Remote sensing of nighttime lights has been shown as a good surrogate for estimating population and economic activity at national and sub-national scales, using DMSP satellites. However, few studies have examined the factors explaining differences in nighttime brightness of cities at a global scale. In this study, we derived quantitative estimates of nighttime lights with the new VIIRS sensor onboard the Suomi NPP satellite in January 2014 and in July 2014, with two variables: mean brightness and percent lit area. We performed a global analysis of all densely populated areas (n=4153, mostly corresponding to metropolitan areas), which we defined using high spatial resolution Landscan population data. National GDP per capita was better in explaining nighttime brightness levels (0.60

Wildfires are expected to increase in Mediterranean landscapes as a result of climate change and changes in land-use practices. In order to advance our understanding of human and physical factors shaping spatial patterns of wildfires in the region, we compared two independently generated datasets of wildfires for Israel that cover approximately the same study period. We generated a site-based dataset containing the location of 10,879 wildfires (1991–2011), and compared it to a dataset of burnt areas derived from MODIS imagery (2000–2011). We hypothesized that the physical and human factors explaining the spatial distribution of burnt areas derived from remote sensing (mostly large fires, >100 ha) will differ from those explaining site-based wildfires recorded by national agencies (mostly small fires, <10 ha). Small wildfires recorded by forestry agencies were concentrated within planted forests and near built-up areas, whereas the largest wildfires were located in more remote region

Artificial night lighting and its negative consequences are of interest in the fields of Astronomy, Human Geography, Ecology and Human Health. The majority of studies to date focused on the impacts light pollution has on our ability to view the night sky, as well as on biodiversity, ecosystems and humans. However, in recent years, with the emergence of new high spatial resolution sensors, providing detailed evaluation of night lights at the local level, more attention has been given for estimating and quantifying artificial light within cities. In this study, we evaluate urban night lights within the city of Jerusalem by combining data from two remote sensing tools: ground measurements using Sky Quality Meter (SQM) devices and space-borne measurements using EROS-B night light imagery. In addition, we examined the use of the SQM for evaluating artificial light in different view directions: upwards, downwards and horizontally. Differences in night lights were found between the three SQM

Geographic information systems allow the extraction and quantitative analysis of information from historical maps. The aims of this research were to examine the completeness of information represented on the 1881 Palestine Exploration Fund (PEF) map, to quantitatively reconstruct the landscape of nineteenth century Palestine and to explore whether spatial patterns in land cover/land use can be partially explained statistically by physical and human factors. Using historical aerial photos, we concluded that most of the major past landscape features were indeed shown on the PEF map, with an average overall correspondence of 53%. Forests and Mediterranean maquis were more abundant at distances greater than 2 km from towns and villages. Specific land cover/land-use types were associated with certain soil types, topographic regions and rainfall thresholds. In conclusion, the 1881 PEF map can serve as a reliable reference for understanding the land cover/land-use patterns of nineteenth cent

Author(s): Salit Kark [sup.1] [sup.2]*, William J. Sutherland [sup.3], Uri Shanas [sup.4], Keren Klass [sup.2] [sup.5], Hila Achisar [sup.2], Tamar Dayan [sup.6], Yael Gavrieli [sup.7], Ronit Justo-Hanani [sup.6], Yael Mandelik [...]