Multi-date Sentinel1 SAR image textures discriminate perennial agroforests in a tropical forest-savannah transition landscape

Autor: R. R. De Wulf, F. Van Coillie, Frederick N. Numbisi

Publikováno v: ISPRS TC I mid-term symposium : innovative sensing : from sensors to methods and applications
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-1, Pp 339-346 (2018)

Synthetic Aperture Radar (SAR) provides consistent information on target land features; especially in tropical conditions that restrain penetration of optical imaging sensors. Because radar response signal is influenced by geometric and di-electrical

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7469890fee844489ce7043f39dc807a3
https://biblio.ugent.be/publication/8635257

Training neural networks on artificially generated data: a novel approach to SAR speckle removal

Autor: F. Van Coillie, Hans Lievens, R. R. De Wulf, Niko E. C. Verhoest, Aleksandra Pizurica, Lieven Verbeke, Isabelle Joos

Publikováno v: International Journal of Remote Sensing. 32:3405-3425

A neural network-based method for speckle removal in synthetic aperture radar (SAR) images is introduced. The method rests on the idea that a neural network learning machine, trained on artificially generated input-target couples, can be used to effi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c0adbda8cf3117a8645ddf175a8efd2c
https://doi.org/10.1080/01431161003749436

Mapping dominant vegetation communities at Meili Snow Mountain, Yunnan Province, China using satellite imagery and plant community data

Autor: E. De Clercq, Xiaokun Ou, Zhiming Zhang, Lieven Verbeke, R. R. De Wulf

Publikováno v: Geocarto International. 23:135-153

Mapping dominant vegetation communities is important work for vegetation scientists. It is very difficult to map dominant vegetation communities using multispectral remote sensing data only, especially in mountain areas. However plant community data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::82e4db606f90ffdf603c845d2c9ed4d9
https://doi.org/10.1080/10106040701337410

Previously trained neural networks as ensemble members: Knowledge extraction and transfer

Autor: Lieven Verbeke, F. Van Coillie, R. R. De Wulf

Publikováno v: International Journal of Remote Sensing. 25:4843-4850

The use of Artificial Neural Networks (ANNs) for the classification of remotely sensed imagery offers several advantages over more conventional methods. Yet their training still requires a set of pixels with known land cover. To increase ANN classifi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f6966a6d22ebecad88892ded22a92054
https://doi.org/10.1080/01431160410001716914

Using genetic algorithms in sub-pixel mapping

Autor: K. C. Mertens, L. P. C. Verbeke, E. I. Ducheyne, R. R. De Wulf

Publikováno v: International Journal of Remote Sensing. 24:4241-4247

In remotely sensed images, mixed pixels will always be present. Soft classification defines the membership degree of these pixels for the different land cover classes. Sub-pixel mapping is a technique designed to use the information contained in thes

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::02f63f783004da98ac08d4eb5724697b
https://doi.org/10.1080/01431160310001595073