Dams constructed by humans are important facilities for irrigation, flood control, and power generation. Recognizing the location number of dams is crucial studying impact human activities on ecosystem change. Although many countries organizations have established their own dam datasets, it only tip iceberg real construction. Therefore, effectively accurately obtaining geographic still a signif...

Fires in the Sardinia Island are one of the most important environmental factors controlling the ecosystem ́s function and structure. The evaluation of fire effects by means of remote sensing is economically and practically the best way to assess fire damage, before going to the field. The use of alternative techniques for fire effects assessment is needed, in particular to characterize the biom...

Change detection of remotely sensed images is a particularly challenging task when the time series data come from different sensors. Indeed, many change indicators are based on radiometry measurements, used to calculate differences or ratios, that are no longer meaningful when the data have been acquired by different instruments. For this reason, it is interesting to study those indicators that...

Convolutional neural networks (CNNs) have achieved great success when characterizing remote sensing (RS) images. However, the lack of sufficient annotated data (together with high complexity RS image domain) often makes supervised and transfer learning schemes limited from an operational perspective. Despite fact that unsupervised methods can potentially relieve these limitations, they are freq...

Due to the limited accuracy of exterior orientation parameters, ground control points (GCPs) are commonly required to correct the geometric biases of remotely-sensed (RS) images. This paper focuses on an automatic matching technique for the specific task of georeferencing RS images and presents a technical frame to match large RS images efficiently using the prior geometric information of the i...

Specific current objectives include: (a) Implementation of a comprehensive coastal prediction system incorporating atmospheric, benthic and bio-optical submodels; (b) Construction of shipboard/autonomous subsurface sampling network beneath spatially extensive remotely sensed surface observations; (c) Development of data-assimilative and visualization interfaces for modeldirected adaptive sampli...

The huge amount of information some of the new optical satellites developed nowadays will create demands to quickly and reliably compensate for changes in the atmospheric transmittance and varying solar illumination conditions. In this paper three different forms of affine transformation models (general, particular and diagonal) are considered as candidates for rapid compensation of illuminatio...