Multi-temporal remote sensing
Multi-Temporal multi-scalar modelling of the dynamics of urban landscape changes by remote sensing
... characterisation (SPOT 6/7, Sentinel 2) • Urban fabric extraction and change detection.. using spectral indices (Sentinel 2).[r] ...
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Agro-hydrology and multi temporal high resolution remote sensing: toward an explicit spatial processes calibration
... 1.4 Objectives The aim of the present study is therefore to explore the ad- vantage of using leaf area index map series, derived from high-resolution RS products, for the spatial representation of the water and nutrient ...
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Change detection in heterogeneous remote sensing images based on multi-dimensional evidential reasoning
... of remote sensing images can share a common frame of discernment if the images are obtained by the same kind of sensors, but they may lie in the different frames once the images are acquired from the ...
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Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration
... 1.4 Objectives The aim of the present study is therefore to explore the ad- vantage of using leaf area index map series, derived from high-resolution RS products, for the spatial representation of the water and nutrient ...
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Hierarchical joint classification models for multi-resolution, multi-temporal and multi-sensor remote sensing images. Application to natural disasters
... données multi-bande, multi-résolution, multi-date et éventuellement multi-capteur tout en gardant un temps de calcul ...classi cation multi-date/multi- capteur et ...
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Remote Sensing of Mountain Permafrost Landscape by Multi-Fusion Data Modeling. Example of Verkhoyansk Ridge (Russia)
... by remote sensing of these five geographic components structuring the permafrost-mountain landscape in Siberian Arctic region allows modeling the evolution of the Arctic landscape and analyses the current ...
5
Riga-Klaipeda Road Corridor Impacts on the Urbanization and Spatial Structures by Multi-Level Sensors Remote Sensing
... 8 -The data geo-referencing: All the image and geographical databases were geo- referenced in UTM North WGPS 84 (areas 34 and 35). The importance of the geo- referencing of all geographic data is twofold: (1) provide ...
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Towards a better understanding of grass bed dynamics using remote sensing at high spatial and temporal resolutions
... uses multi-temporal information to detect clouds and clouds' shadows to estimate the optical properties of the ...high temporal frequency of the Sentinel-2 instrument, we could work with a ...
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Scalable Bag of Subpaths Kernel for Learning on Hierarchical Image Representations and Multi-Source Remote Sensing Data Classification
... for remote sensing data fusion in a recent survey paper [ 13 ], as they offer a general framework allowing one to fuse different sources of information in a classification ...from multi-source [ 30 ] ...
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Remote Sensing of Industrial Palm Groves in Cameroon
... Prune Christobelle Komba Mayossa et al.: Remote Sensing of Industrial Palm Groves in Cameroon Figure 4. Land cover map from Spot6 (2015) CNRS ESPACE UMR 7300. Highly correlated maps with overall accuracies ...
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Optimal Transport for Data Fusion in Remote Sensing
... 3 MMRS/University of Zurich, Zurich, Switzerland 4 LETG/CNRS, Rennes, France ABSTRACT One of the main objective of data fusion is the integration of several acquisition of the same physical object, in order to build a ...
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Spatial and temporal variability of land CO 2 fluxes estimated with remote sensing and analysis data over western Eurasia
... 2.3.1. NDVI. The TURC model is driven by NDVI (Normalized Difference Vegetation Index) from the VEGETATION sensor on-board SPOT4 satellite. Since April 1998, VEGETATION provides a daily coverage of the earth with a 1 km ...
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Remote sensing and air quality in urban areas
... 16. FINZI, G., LECHI, G.M.,: Landsat images of urban air pollution in stable meteorological conditions, Il Nuovo Cimento, 14C, (1991) 433-443 17. BRIVIO, P.A., GENOVESE, G., MASSARI, S., MILEO, N., SAURA, G., ZILIOLI, ...
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Mobile and remote inertial sensing with atom interferometers
... and remote inertial sensing with cold atoms promises a new era of measurements for both applied and fundamental ...prospecting, remote object detection, and tidal chart correction—they may one day ...
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Automatic Vehicle Trajectory Extraction by Aerial Remote Sensing
... in sensing technologies and image processing algorithms reduced the resources (time and costs) required for detailed traffic data collection, promoting the feasibility of site-based and vehicle-based naturalistic ...
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Characterizing the complexity of landscape boundaries by remote sensing
... Keywords: boundary, covert, landscape indices, landscape physiognomy, fragmentation, diversity, remote sensing Abstract This paper presents a method for characterizing the complexity of landscape boundaries ...
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A Semantic Retrieval System for Remote Sensing Web Platforms
... How to program computers to process and analyze large amounts of natural language data.... Workflow[r] ...
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Learning approaches for large-scale remote sensing image classification
... deep multi-layer schemes with downsampling because we actually consider that certain objects can only be detected at the upper layers of the network, when a large amount of context has been taken into account and ...
159
Polygonization of Remote Sensing Classification Maps by Mesh Approximation
... 6. CONCLUDING REMARKS We presented a mesh approximation algorithm to polygonize remote sensing classification maps. The polygonal objects are more accurate than the current methods used in the GIS ...
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Retrieval of Remote Sensing Images with Pattern Spectra Descriptors
... the multi-variate structure of remote sensing images, which nowadays routinely reaches the level of hundreds of bands in the case of hyperspectral ...
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