Image retrieval from remote sensing big data: A survey
The blooming proliferation of aeronautics and astronautics platforms, together with the ever-
increasing remote sensing imaging sensors on these platforms, has led to the formation of …
increasing remote sensing imaging sensors on these platforms, has led to the formation of …
Feature mining for hyperspectral image classification
Hyperspectral sensors record the reflectance from the Earth's surface over the full range of
solar wavelengths with high spectral resolution. The resulting high-dimensional data contain …
solar wavelengths with high spectral resolution. The resulting high-dimensional data contain …
Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?
The geospatial sciences face grand information technology (IT) challenges in the twenty-first
century: data intensity, computing intensity, concurrent access intensity and spatiotemporal …
century: data intensity, computing intensity, concurrent access intensity and spatiotemporal …
Using artificial intelligence for space challenges: A survey
A Russo, G Lax - Applied Sciences, 2022 - mdpi.com
Artificial intelligence is applied to many fields and contributes to many important applications
and research areas, such as intelligent data processing, natural language processing …
and research areas, such as intelligent data processing, natural language processing …
A review of EO image information mining
M Quartulli, IG Olaizola - ISPRS journal of Photogrammetry and Remote …, 2013 - Elsevier
We analyze the state of the art of content-based retrieval in Earth observation image
archives focusing on complete systems showing promise for operational implementation …
archives focusing on complete systems showing promise for operational implementation …
Support vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer
The retrieval of biophysical variables using canopy reflectance models is hindered by the
fact that the inverse problem is ill posed. This is due to the measurement, model errors and …
fact that the inverse problem is ill posed. This is due to the measurement, model errors and …
[PDF][PDF] Exploiting deep features for remote sensing image retrieval: A systematic investigation
Remote sensing (RS) image retrieval based on visual content is of great significance for
geological information mining. Over the past two decades, a large amount of research on …
geological information mining. Over the past two decades, a large amount of research on …
Object-oriented classification of high-resolution remote sensing imagery based on an improved colour structure code and a support vector machine
H Li, H Gu, Y Han, J Yang - International journal of remote sensing, 2010 - Taylor & Francis
This paper presents a new object-oriented land cover classification method that integrates
raster analysis and vector analysis. The method adopts an improved colour structure code …
raster analysis and vector analysis. The method adopts an improved colour structure code …
Localized homology
A Zomorodian, G Carlsson - Computational Geometry, 2008 - Elsevier
In this paper, we provide the theoretical foundation and an effective algorithm for localizing
topological attributes such as tunnels and voids. Unlike previous work that focused on 2 …
topological attributes such as tunnels and voids. Unlike previous work that focused on 2 …
A machine learning based spatio-temporal data mining approach for detection of harmful algal blooms in the Gulf of Mexico
Harmful algal blooms (HABs) pose an enormous threat to the US marine habitation and
economy in the coastal waters. Federal and state coastal administrators have been devising …
economy in the coastal waters. Federal and state coastal administrators have been devising …