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The HYEP project (ANR HYEP 14-CE22-0016-01 Hyperspectral imagery for Environmental urban Planning - Mobility and Urban Systems Programme - 2014) confirmed the interest of a global approach to the urban environment by remote sensing and in particular by using hyperspectral imaging (HI). The interest of hyperspectral images lies in the range of information provided over wavelengths from 0.4 to 4 μm; they thus provide access to spectral quantities of interest and to chemical or biophysical parameters of the surface. HYEP's objective was to specify this and to propose a panel of methods and treatments taking into account the characteristics of other existing sensors in order to compare their performance. The developments carried out were applied and evaluated on hyperspectral airborne images acquired in Toulouse and Kaunas (Lithuania), also used to synthesize space systems: Sentinel-2, Hypxim/Biodiversity and Pleiades. Among the locks identified were those related to improving the spatial capabilities of the sensors and spatial scale changes, which were partially overcome by fusion and sharpening approaches, which proved to be successful. After a description of our hyperspectral data set acquired over Toulouse, an analysis is conducted on several existing and accessible spectral databases. Then, the chosen methods are presented. They include extraction, fusion and classification methods, which are then applied on our dataset synthetized at different spatial resolution to evaluate the benefits and the complementarity of hyperspectral imagery in comparison with other traditional sensors. Some specific applications are investigated of interest for urban planners: impervious soil map, vegetation species cartography and detection of solar panels. Finally, discussion and perspectives are presented. [ABSTRACT FROM AUTHOR]

The mapping of the land use of Gabon in 2010 and 2015 and the changes between these two dates was carried out as part of the OSFACO program (Space observation of Central and Western African Forests) by the Gabonese Agency for Space Studies and Observations (AGEOS). This is the first reference land use map at the national level, including the legend resulting from a consultation of major players in the Gabonese forest sector. This map was obtained by refining the forest cover map of Gabon (forest/non-forest) obtained in the framework of OSFT (Spatial Observation of Tropical Forests) and GEOFORAFRI project (Capacity building and access to earth observation satellite data for monitoring forests in Central and Western Africa). The mapping was based on the use of SPOT 5/7, Sentinel 2 satellite images for the year 2015 and the SPOT 4, ASTER and ALOS 1 images for the year 2010. Semi-automated classification method and Manual enhancement were combined for better accuracy of land use classes. The results obtained highlight ten land use classes representing the country's large landscape groups dominated by forests which occupied 89% of the total area of the country in 2015. The most dynamic land use classes are forests, savannas, agricultural land and artificial surfaces. The main forest losses are linked to the conversion of forests to artificial surfaces, cultivated land and bare soils. The most significant gains in forest are observed at the level of the closure of forest roads. The validation of the product, carried out by an independent expertise from the map production team, was based on a reference data resulting from a sampling plan combining a systematic and random component according to the methodology of Sannier et al. (2016). The analysis of the correspondence between the land use map produced and the reference data gave an overall accuracy of 95%. [ABSTRACT FROM AUTHOR]

Remote sensing is a particularly suitable tool for monitoring land use but also particularly suited for déforestation monito-ring. By launching the Setinel-1 and Sentinel-2 satellites in the Copernicus program, the community now has free data with important time-revisits allowing the greatest number of people to effectively monitor land cover of a study area. This paper présents a land use monitoring method based on the combination of two approaches computed using Open Source tools (QGIS, Orfeo ToolBox, python). First, we focus on land use monitoring at an annual time scale using Sentinel-1 and Sentinel-2 data, and then, by the use f entienl-1 data, we detect changes in the forest cover due to déforestation at bi-monthly time scale. The results obtained show a very good synergy of thèse approaches allowing the complementary of optical and radar data. In order to make accessible the proposed method, ail the used open source tools are available on this link http ://remotesensing4all.net/index.php/2018/09/11/kit-use-des-donnees-radar-sentinel-1-in-de-latelier-radar-du-FOSS4G-en-2018-2/. [ABSTRACT FROM AUTHOR]