Archived Satellite Imagery Research Articles

Using commercial high-resolution satellite imagery to monitor a nuisance macroalga in the largest marine protected area in the USA

Satellite imagery is a useful tool for monitoring and mapping the distribution of invasive or nuisance algal species on coral reefs over the temporal and spatial scales needed for ecosystem management. Visual inspections of high-resolution satellite imagery were used to detect the newly discovered nuisance alga, Chondria tumulosa, at Manawai (Pearl and Hermes Atoll) in combination with ground-truthing surveys. Low-albedo (“dark”) survey sites on spur habitats were associated with mean C. tumulosa cover seven times higher than adjacent high-albedo (“light”) sites. There was an inverse relationship between C. tumulosa percent cover at ground-truthing sites and mean reflectance values. Archival satellite imagery showed that areas of high C. tumulosa cover (i.e., dark patches) were not evident on or before 2015 on the northeast backreef. The ability to use satellites for the detection of nuisance or invasive benthic species, such as expansive mats of C. tumulosa, provides managers with a valuable tool, especially in remote regions.

Remote sensing and the UN Ocean Decade: high expectations, big opportunities

Remote sensing and the UN Ocean Decade: high expectations, big opportunities

Satellite Remote Sensing for the Analysis of the Micia and Germisara Archaeological Sites

The capabilities of satellite remote sensing technologies and their derived data for the analysis of archaeological sites have been demonstrated in a large variety of studies over the last decades. Likewise, the Earth Observation (EO) data contribute to the disaster management process through the provision of updated information for areas under investigation. In addition, long term studies may be performed for the in–depth analysis of the disaster–prone areas using archive satellite imagery and other cartographic materials. Hence, satellite remote sensing represents an essential tool for the study of hazards in cultural heritage sites and landscapes. Depending on the size of the archaeological sites and considering the fact that some parts of the site might be covered, the main concern regards the suitability of satellite data in terms of spatial and spectral resolution. Using a multi–temporal Sentinel–2 dataset between 2016 and 2019, the present study focuses on the hazard risk identification for the Micia and Germisara archaeological sites in Romania as they are endangered by industrialisation and major infrastructure works and soil erosion, respectively. Furthermore, the study includes a performance assessment of remote sensing vegetation indices for the detection of buried structures. The results clearly indicate that Sentinel–2 imagery proved to be fundamental in meeting the objectives of the study, particularly due to the extensive archaeological knowledge that was available for the cultural heritage sites. The main conclusion to be drawn is that satellite–derived products may be enhanced by integrating valuable archaeological context, especially when the resolution of satellite data is not ideally fitting the peculiarities (e.g., in terms of size, underground structures, type of coverage) of the investigated cultural heritage sites.

Применение ГИС-технологий для изучения территорий археологического наследия: пример сельской округи Херсонеса Таврического, Крым

Archaeological postagrogenic landscapes are characterized by large heterogeneity of soil and vegetation cover and variability of soil properties, which is due to the long history and evolution of agricultural practices. The study of such territories is promising, using the capabilities of GIS technologies and geostatistical analysis for visualization and subsequent meaningful interpretation of spatially distributed information. The purpose of the research was the first study and a comprehensive assessment of the maturity of the soil and vegetation cover of the still preserved steppe ecosystems (on an area of about 760 ha) in the ancient allotments of Tauric Chersonesos (South-Western Crimea), which were created in the 4th century BC and have been used for over four centuries. Geoinformation analysis made it possible to establish the basic territorial patterns of distribution of indicators of the land cover (organic carbon content, C:N ratio, soil colour, soil red index, projective cover with feather grass, its height and projective cover with steppe litter) and their integral estimates for a potential agricultural zone Chersonesos, which is considered to be included in the land cadastral system of the state. The frequency of distribution of the grape plantation within the boundaries of the allotments decreases in the direction from northwest to southeast, which was established using archival satellite imagery and aerial photography on the territory of the rural district of Chersonesos (chora). This regularity could be reflected in the properties of plantation ploughing soils that in ancient times were turbocharged to a depth of 60–70 cm (more clarified by colour, less humus), and more often represented by remote sensing data in the north-western and central part of the rural district of Chersonesos. The performed geoinformation analysis of spatially distributed information on the colour, content of Corg, and C:N values in fallow soils and vegetation cover indicators confirmed the need to divide the chora into two agro-economic zones, which reflect differences in the specialization of agriculture (perennial plantations closer to the city (orchards and vineyards) and remote land in the southeast with predominantly grain farming). The use of spatial analysis tools to study ancient agricultural regions has new opportunities for identifying patterns in the heterogeneity of soil and vegetation, which allows it to be recommended for multidisciplinary studies of other postagrogenic landscapes of the ancient world.

Space technology meets policy: An overview of Earth Observation sensors for monitoring of cultural landscapes within policy framework for Cultural Heritage

A wide range of satellite sensors that provide potentially useful imagery for digital documentation, mapping and monitoring of archaeological sites and cultural landscapes. Although some satellites have stopped acquiring new data, their archived satellite imagery can still be accessed, downloaded and exploited for monitoring of changes and therefore useful for research domain of archaeology and cultural landscapes. The aim of this paper is 1) to make an overview of past and current satellite earth observation optical sensors useful for land monitoring, with focus on cultural landscapes and 2) to illustrate a policy framework that goes beyond recommendations, suggesting the need of valuable information possibly provided by the in satellite imagery. Paper will put focus on Copernicus programme as the most recent mission that provides imagery on the global scale and free of charge. Paper, furthermore, highlights the need for a more structured consideration of the contribution that space technologies services and products can offer to the non-space sectors. The actions for implementation of strategies regarding the currently renewed attention towards cultural heritage protection and management, could soon benefit from the technological achievements of satellite technologies in terms of dedicated operational services and applications, tailored to the needs of end-users such as archaeologists, landscape professionals, public administration, researchers and students.

Climate warming causes intensification of the hydrological cycle, resulting in changes to the vernal and autumnal windows in a northern temperate forest

AbstractClimate warming is likely to lead to complex effects on northern forests of the temperate forest biome. We investigated whether rising temperatures altered the timing of snowmelt and snowpack accumulation or extended the forest growing season length in the Turkey Lakes Watershed in central Ontario. Archived satellite imagery was used to track changes in timing of snowpack loss/gain and canopy leaf on/off; the periods between these events were defined as the vernal (spring) and autumnal (fall) windows. We found only a slight extension of the growing season into the autumn period and no increase in the width of the vernal or autumnal windows, indicating that forest growth is not responding significantly to temperature increases during these windows. Archived time series of temperature, precipitation and discharge data for a nested set of catchments ranging in size from headwater (<10 ha) to regional (103 ha) catchments were used to track changes in the magnitude, timing and partitioning of precipitation into evapotranspiration and discharge. We found an intensification of hydrological cycling, with (1) a higher dryness index (PET/P) during the summer growing season and (2) earlier spring snowmelt discharges, and later more concentrated autumn storm discharges during the shoulder seasons. This intensification of the hydrological cycle during the summer growth season and the vernal and autumnal windows may not only limit opportunities for enhanced forest growth, but may be contributing to the recent observations of forest decline within this biome. Copyright © 2015 John Wiley & Sons, Ltd.

Monitoring disease trends using hospital traffic data from high resolution satellite imagery: a feasibility study.

Challenges with alternative data sources for disease surveillance include differentiating the signal from the noise, and obtaining information from data constrained settings. For the latter, events such as increases in hospital traffic could serve as early indicators of social disruption resulting from disease. In this study, we evaluate the feasibility of using hospital parking lot traffic data extracted from high-resolution satellite imagery to augment public health disease surveillance in Chile, Argentina and Mexico. We used archived satellite imagery collected from January 2010 to May 2013 and data on the incidence of respiratory virus illnesses from the Pan American Health Organization as a reference. We developed dynamical Elastic Net multivariable linear regression models to estimate the incidence of respiratory virus illnesses using hospital traffic and assessed how to minimize the effects of noise on the models. We noted that predictions based on models fitted using a sample of observations were better. The results were consistent across countries with selected models having reasonably low normalized root-mean-squared errors and high correlations for both the fits and predictions. The observations from this study suggest that if properly procured and combined with other information, this data source could be useful for monitoring disease trends.

Linking spatial inundation indicators and hydrological modelling to improve assessment of inundation extent

Environmental water requirements (EWRs), including past inundation regimes, provide useful information for the conservation and management of wetlands systems. However, determining past inundation regimes is difficult as very few wetlands have historical records of water level or flow to determine EWRs. Generally, two approaches have been used to reconstruct wetland inundation regimes; remote sensing or hydrological modelling. Remote sensing methods have applied spectral indices of inundation to multi-temporal archival satellite imagery and developed simple empirical models to link inundation extent to rainfall or stream flow records. Hydrological models use a water balance approach and simple relationships between volume and area based on the wetland bathymetry to derive an inundation regime. While remote sensing approaches can provide a high spatial resolution of information, the temporal resolution is limited to an image every few weeks, and the usability of each image is subject to cloud cover. Hydrological models require some data in the region of interest for calibration, and often the model is not sensitive to the inundation variables of interest when calibrating to the data available. A study is presented where this is the case, where good results are achieved by a hydrological model when compared to downstream flow data, but very different wetland inundation regimes can be simulated. Due to this limitation, the remotely-sensed inundation regime was required as another source of information to calibrate the hydrological model, constraining the parameters involved in the modelled wetland storages. The remote-sensing constrained hydrological model provided greater confidence in the representation of processes occurring in the simulated wetland storages, and hence could be considered appropriate to be applied to a validation time period and for scenario testing. The findings of this research support the combination of remotely sensed indicators of inundation and hydrological modelling to increase confidence in the spatial representation of the dynamics of inundation. Understanding wetland inundation dynamics is critical to the understanding and management of threatened wetland ecosystems. Hence, the methods outlined in paper will ultimately assist in informing better management of wetlands.

Quantifying tree mortality in a mixed species woodland using multitemporal high spatial resolution satellite imagery

Widespread tree mortality events have recently been observed in several biomes. To effectively quantify the severity and extent of these events, tools that allow for rapid assessment at the landscape scale are required. Past studies using high spatial resolution satellite imagery have primarily focused on detecting green, red, and gray tree canopies during and shortly after tree damage or mortality has occurred. However, detecting trees in various stages of death is not always possible due to limited availability of archived satellite imagery. Here we assess the capability of high spatial resolution satellite imagery for tree mortality detection in a southwestern U.S. mixed species woodland using archived satellite images acquired prior to mortality and well after dead trees had dropped their leaves. We developed a multistep classification approach that uses: supervised masking of non-tree image elements; bi-temporal (pre- and post-mortality) differencing of normalized difference vegetation index (NDVI) and red:green ratio (RGI); and unsupervised multivariate clustering of pixels into live and dead tree classes using a Gaussian mixture model. Classification accuracies were improved in a final step by tuning the rules of pixel classification using the posterior probabilities of class membership obtained from the Gaussian mixture model. Classifications were produced for two images acquired post-mortality with overall accuracies of 97.9% and 98.5%, respectively. Classified images were combined with land cover data to characterize the spatiotemporal characteristics of tree mortality across areas with differences in tree species composition. We found that 38% of tree crown area was lost during the drought period between 2002 and 2006. The majority of tree mortality during this period was concentrated in piñon-juniper (Pinus edulis-Juniperus monosperma) woodlands. An additional 20% of the tree canopy died or was removed between 2006 and 2011, primarily in areas experiencing wildfire and management activity. -Our results demonstrate that unsupervised clustering of bi-temporal NDVI and RGI differences can be used to detect tree mortality resulting from numerous causes and in several forest cover types.

SEMI-AUTOMATED CLOUD/SHADOW REMOVAL AND LAND COVER CHANGE DETECTION USING SATELLITE IMAGERY

Abstract. Multi-platform/sensor and multi-temporal satellite data facilitates analysis of successive change/monitoring over the longer period and there by forest biomass helping REDD mechanism. The historical archive satellite imagery, specifically Landsat, can play an important role for historical trend analysis of forest cover change at national level. Whereas the fresh high resolution satellite, such as ALOS, imagery can be used for detailed analysis of present forest cover status. ALOS satellite imagery is most suitable as it offers data with optical (AVNIR-2) as well as SAR (PALSAR) sensors. AVNIR-2 providing data in multispectral modes play due role in extracting forest information. In this study, a semi-automated approach has been devised for cloud/shadow and haze removal and land cover change detection. Cloud/shadow pixels are replaced by free pixels of same image with the help of PALSAR image. The tracking of pixel based land cover change for the 1995-2009 period in combination of Landsat and latest ALOS data from its AVNIR-2 for the tropical rain forest area has been carried out using Decision Tree Classifiers followed by un-supervised classification. As threshold for tree classifier, criteria of NDVI refined by reflectance value has been employed. The result shows all pixels have been successfully registered to the pre-defined 6 categories; in accordance with IPCC definition; of land cover types with an overall accuracy 80 percent.

Defining protected area boundaries based on vascular-plant species richness using hydrological information derived from archived satellite imagery

Surface and near-surface hydrological conditions are not generally considered in the selection of protected-area boundaries; however, these hydrological conditions may be critical in the maintenance of hydrologically driven biodiversity areas and should factor heavily in systematic conservation planning and impact-mitigation efforts. Here we demonstrate the use of Synthetic Aperture Radar (SAR) satellite imagery to model surface and near-surface hydrological dynamics and related vascular-plant species richness surrounding Sundance Provincial Park, Alberta, Canada. Based on a relationship established between field-sampled soil moisture and remote-sensed SAR backscatter coefficient, we generated landscape-scale maps of surface hydrological condition and related vascular-plant species richness surrounding the protected area. After processing, SAR data were classified into three hydrological classes: unsaturated, saturated and inundated. By assembling a multi-year series of SAR images acquired across the natural range of hydrological conditions, the probability of surface saturation and inundation was developed. Using the resulting probability map to select sites for biodiversity assessment, we found relatively strong relationships between total vascular plants (species richness, especially ferns and herbs), and the probability of wet area (both saturated and inundated areas) occurrence. Using this relationship, we mapped vascular-plant species richness across the study region revealing opportunities to mitigate impacts from adjacent developments and to expand the park to increase its ecological value. This study presents an important approach for assessing biodiversity of existing parks and generating valuable input layers that help to define ecologically relevant protected-area boundaries.

The role of baroclinic waves in the initiation of tropical cyclones across the southern Indian Ocean

AbstractCases where tropical storms are initiated simultaneously along one latitude are investigated. It is argued that such structure arises as part of a baroclinic wave. A case from February 2008 is examined using European Centre for Medium‐Range Forecasts (ECMWF) analyses; the birth of three tropical cyclones in the low‐level cyclonic regions to the east of upper‐level troughs suggests that the wave was instrumental for initiation. Archived satellite imagery and storm warnings reveal that baroclinic waves over the southern Indian Ocean accompany tropical cyclogenesis twice a season on average, mainly in late summer, when breaking Rossby waves on the subtropical westerly jet are closest to the Intertropical Convergence Zone (ITCZ). Copyright © 2012 Royal Meteorological Society