Accurately quantifying the vegetation rainfall interception at a high resolution is critical for rainfall-runoff modeling and flood forecasting, and is also essential for understanding its further impact on local, regional, and even global water cycle dynamics. In this study, the Remote Sensing-based Gash model (RS-Gash model) is developed based on a modified Gash model for interception loss es...

We present a complete processing line to enhance large Remote Sensing (RS) image databases in the framework of real-time 3D rendering. RS and Virtual Reality communities are faced to several challenges to deal in real-time with large image datasets while preserving high quality and realistic rendering. There is an increasing interest of InSAR (Interferometric Synthetic Aperture Radar) data, due...

The approach of using multispectral remote sensing (RS) to estimate soil available nutrients (SANs) has been recently developed and shows promising results. This method overcomes the limitations of commonly used methods by building a statistical model that connects RS-based crop growth and nutrient content. However, the stability and accuracy of this model require improvement. In this article, ...

Remote Sensing (RS) refers to the science of identification of earth surface features and estimation of their geo-biophysical properties using electromagnetic radiation as a medium of interaction. Spectral, spatial, temporal and polarization signatures are major characteristics of the sensor/target, which facilitate target discrimination. Earth surface data as seen by the sensors in different w...

Deep neural networks have achieved great success in many important remote sensing tasks. Nevertheless, their vulnerability to adversarial examples should not be neglected. In this study, we systematically analyze the Universal Adversarial Examples Remote Sensing (UAE-RS) data for first time, without any knowledge from victim model. Specifically, propose a novel black-box attack method, namely, ...

Two methods of grid based and image based modeling were put forward respectively to represent the landform of watersheds on the Loess Plateau, China. Many kinds of spatial data such as Digital Elevation Model (DEM), Remote Sensing (RS) images, and photos are utilized to establish the digital 3-D terrains of watersheds on the Loess Plateau, which provides 3-D virtual geographic environments for ...

This paper gives an overview of the recent progress made in the use and application of geographical information systems (GIS) and remotely sensed (RS) satellite sensor data for the epidemiology and control of schistosomiasis in sub-Saharan Africa. Details are given of the use of GIS to collate, map and analyse available parasitological data. The use of RS data to understand better the broad sca...

Earth observation from space involves accessing, sharing, and processing huge volumes of data collected from satellite sensors. It is crucial for users to easily analyze and process the datasets, which may require complex computation on very high volume datasets, particularly for large-scale spatio-temporal analysis. Generation of data products, access to, analysis and visualization of these la...

The use of new technologies including Geographic Information Systems (GIS), the Global Positioning System (GPS), Variable Rate Technology (VRT), and Remote Sensing (RS) is gaining acceptance in the present high-technology, precision agricultural industry. GIS provides the ability to link multiple data values for the same geo-referenced location, and provides the user with a graphical visualizat...

This paper describes how Volunteered Geographic Information (VGI) can support automatic information retrieval (IR) from big remote sensing (RS) data on an example of the Global Human Settlement Layer (GHSL)[1]. Here, the OpenStreetMap 1 (OSM) derived data are used within a satellite imagery processing framework at several stages of an information layer production. Although, we focus on built-up...