Evaluation of MODIS data for mapping oil slicks - the deepwater horizon oil spill case

Moderate Resolution Imaging Spectroradiometer (MODIS) multispectral imagery is used for oil spills mapping as an integration to radar data. MODIS images of the northern Gulf of Mexico (USA) are analyzed to study the sea anomalies from visible to thermal infrared in order to detect a reported oil slick. A simple Fluorescence/Emissivity Index and RGB false color bands combination are applied to detect fluorescence and emissivity anomalies due to oil spills in particular sun glint conditions. A monitoring system of sea surface may be built using high temporal resolution imagery as MODIS data. Applying the proposed index and RGB bands combination, also suitable on night-time overpasses, it’s possible to further increase the availability of clouds free images using optical sensors

Petroleum exploration in Africa from space

Hydrocarbons are nonrenewable resources but today they are the cheaper and easier energy we have access and will remain the main source of energy for this century. Nevertheless, their exploration is extremely high-risk, very expensive and time consuming. In this context, satellite technologies for Earth observation can play a fundamental role by making hydrocarbon exploration more efficient, economical and much more eco-friendly. Complementary to traditional geophysical methods such as gravity and magnetic (gravmag) surveys, satellite remote sensing can be used to detect onshore long-term biochemical and geochemical alterations on the environment produced by invisible small fluxes of light hydrocarbons migrating from the underground deposits to the surface, known as microseepage effect. This paper describes two case studies: one in South Sudan and another in Mozambique. Results show how remote sensing is a powerful technology for detecting active petroleum systems, thus supporting hydrocarbon exploration in remote or hardly accessible areas and without the need of any exploration license

Supporting hydrocarbon exploration in new venture areas with optical remote sensing

In past time, exploration geologists mainly used Earth Observation systems for basin-wide analysis of gravimetry, magnetomerty, structural faults, lithology and land-cover. After two decades of research, nowadays multispectral and hyperspectral remote sensing represent a cutting-edge technology in the oil and gas industry. The application fields of optical remote sensing not only range from the monitoring of the oilfields to the evaluation of pollution, but also to hydrocarbon exploration. With reference to exploration activities, the observation of the territory from above into several different wavelengths is able to supply inestimable geophysical information related to the microseepage effect, different and complementary to tradition geophysical methods. It is almost accepted that many of the oil and gas fields leak light hydrocarbon gases along nearly vertical pathways and, thus, their detection with multi/hyperspectral imaging can support the detection of active petroleum systems. Indeed, several independent oil companies are using satellite and airborne observations for reducing exploration risks in new venture areas and for optimizing their seismic surveys. This study shows some examples of microseepage-related geochemical and geobotanical alterations detected in several different environments, from sandy desert to vegetated savannah, both using airborne hyperspectral data and multispectral satellite time series. All the examples analyze real onshore concession blocks in Africa and Asia and results clearly show a correlation between the spectral signals recorded form remote with in situ measures, well logs, the knowledge of the subsurface and the position of known oilfields

Analysis of changes in crop farming in the Dudh Koshi (Nepal) driven by climate changes

Nepal is one of the poorest nations of the world and the Koshi Basin includes some of the poorest regions of this country. It's farming system is subsistence agriculture, mainly rainfed, with crop productivity among the lowest in South Asia. Nepal is also severely impacted by climate changes, such as retreat of glaciers, rise in temperature, erratic rainfalls and increase in frequency of extreme weather. This paper describes the spatio-temporal evolution of cultivated land in Dudh Koshi during the last four decades (1970s-2010s), by mapping the farming of its four main cereals in the districts of Solukhumbu, Okhaldunga and Kothang from space. The analysis of satellite time series showed a 10% of increment in farmland from 1970s to 1990s, and about 60% in the following twenty years. With a shift of cropping to higher altitudes. Data belonging to of the second twenty years are strongly correlated with the population growth observed in the same period (0.97<0.99) and consistent with the average daily caloric intake. Finding confirms the result of recent studies that agriculture practices once distributed in lowland areas have now spread to higher altitudes and seems to suggest that demographic and socioeconomic pressures are driving the expansion, while climatic and topographic parameters are just channeling the expansion. Apart from any policies that could change the tack, Dudh Koshi should be able to meet the increasing demand of cereals in the near future and climate seems not being a limiting factor for further development as it will be the availability of an irrigation system

Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques

Land-cover/land-use thematic maps are a major need in urban and country planning. This paper demonstrates the capabilities of Object Based Image Analysis in multi-scale thematic classification of a complex sub-urban landscape with simultaneous presence of agricultural, residential and industrial areas using pan-sharpened very high resolution satellite imagery. The classification process was carried out step by step through the creation of different hierarchical segmentation levels and exploiting spectral, geometric and relational features. The framework returned a detailed land-cover/land-use map with a Cohen’s kappa coefficient of 0.84 and an overall accuracy of 85%

Human neural stem cell transplantation in ALS: initial results from a phase I trial

We report the initial results from a phase I clinical trial for ALS. We transplanted GMP-grade, fetal human neural stem cells from natural in utero death (hNSCs) into the anterior horns of the spinal cord to test for the safety of both cells and neurosurgical procedures in these patients. The trial was approved by the Istituto Superiore di Sanit\ue0 and the competent Ethics Committees and was monitored by an external Safety Board

Optimal spectral band configuration for forest land-cover classification of hyperspectral data: a study for the Italian-Canadian Joint Hyperspectral Mission

In 2006 the Italian and the Canadian Space Agencies started a collaboration to evaluate the feasibility of the Joint Hyperspectral Mission (JHM), a new mission for Earth Observation devoted to environmental applications. JHM was designed to operate with a 30 m resolution hyperspectral sensor able to collect 210 narrow spectral bands in the range of 400-2500 nm. This paper presents a study carried on for the Italian Space Agency during Phase A, aimed to suggest an optimal spectral setup for the land-cover key application. Just referring to the mapping of forest species, results on simulated JHM data suggested that an optimal configuration can be obtained using a 50 nm bandwidth

Subpixel geocoding of COSMO-SkyMed and Sentinel-1 time series imaged with different geometry

This paper describes the use of a new multi-image co-registration method tuned for SAR multi-temporal data collected with different orbits, viewing angles and polarization. Tests were performed using COSMO-SkyMed (X-band) and Sentinel-1 data (C-band) time series imaged in stripmap and spotlight modes. Results shows an overview sub-pixel accuracy also for the challenging co-registration of dual orbit image stacks (ascending vs. descending), where other methods fail

Mapping large-scale microseepage signals for supporting oil and gas exploration in new ventures

Optical remote sensing is emerging among non-conventional geophysical methods for oil & gas exploration and mineral prospecting. Complementary to all traditional technologies such as seismic, magnetic, gravity or electric methods, multispectral imaging is able to detect long-term biochemical and geochemical environmental alterations, known as microseepage effect, produced by invisible small fluxes of light hydrocarbons migrating from the underground deposits to the surface. This paper describes a case study where satellite multispectral data were used to detect large-scale microseepage signals nearby Lake Turkana (Republic of Kenya). The satellite analysis highlighted the presence of invisible surface signals on top of several oilfields discovered only many years after the image collection

Detection of moving vehicles with WorldView-2 satellite data

Traffic monitoring in urban areas is a complex issue and recent Remote Sensing technologies can play an important role in planning and monitoring the urban environment. In this study a semi-automatic object-oriented workflow was designed to detect moving vehicles and their speed from single pass WorldView-2 multispectral data. The time lag in data recording between each spectral band causes a small image displacement of moving objects and this discrepancy is used to detect moving vehicles, their speed and direction of travel. The method proposed was applied to a very complex study area in the historical core of city of Multan, in the Pakistani southern province of Punjab, where very small and extremely dense built-up old style houses are mixed together with narrow roads and bazaar streets. First results show interesting applications of this new technology, with achieved accuracies of about 67% evaluated comparing automatic detection vs. manual interpretation