Data-and knowledge-driven mineral prospectivity maps for Canada's North

JR Harris, E Grunsky, P Behnia, D Corrigan - Ore Geology Reviews, 2015‏ - Elsevier
Data-and knowledge-driven techniques are used to produce regional Au prospectivity maps
of a portion of Melville Peninsula, Northern Canada using geophysical and geochemical …

Comparing machine learning classifiers for object-based land cover classification using very high resolution imagery

Y Qian, W Zhou, J Yan, W Li, L Han - Remote sensing, 2014‏ - mdpi.com
This study evaluates and compares the performance of four machine learning classifiers—
support vector machine (SVM), normal Bayes (NB), classification and regression tree …

[HTML][HTML] Comparison of classification algorithms and training sample sizes in urban land classification with Landsat thematic mapper imagery

C Li, J Wang, L Wang, L Hu, P Gong - Remote sensing, 2014‏ - mdpi.com
Although a large number of new image classification algorithms have been developed, they
are rarely tested with the same classification task. In this research, with the same Landsat …

Feature selection for classification of hyperspectral data by SVM

M Pal, GM Foody - IEEE Transactions on Geoscience and …, 2010‏ - ieeexplore.ieee.org
Support vector machines (SVM) are attractive for the classification of remotely sensed data
with some claims that the method is insensitive to the dimensionality of the data and …

Map** paddy rice by the object-based random forest method using time series Sentinel-1/Sentinel-2 data

Y Cai, H Lin, M Zhang - Advances in Space Research, 2019‏ - Elsevier
Rice is one of the world's major staple foods, especially in China. In this study, we proposed
an object-based random forest (RF) method for paddy rice map** using time series …

Analysis of time-series MODIS 250 m vegetation index data for crop classification in the US Central Great Plains

BD Wardlow, SL Egbert, JH Kastens - Remote sensing of environment, 2007‏ - Elsevier
The global environmental change research community requires improved and up-to-date
land use/land cover (LULC) datasets at regional to global scales to support a variety of …

[HTML][HTML] Feature selection of time series MODIS data for early crop classification using random forest: A case study in Kansas, USA

P Hao, Y Zhan, L Wang, Z Niu, M Shakir - Remote Sensing, 2015‏ - mdpi.com
Currently, accurate information on crop area coverage is vital for food security and industry,
and there is strong demand for timely crop map**. In this study, we used MODIS time …

[کتاب][B] Image analysis, classification and change detection in remote sensing: with algorithms for Python

MJ Canty - 2019‏ - taylorfrancis.com
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms
for Python, Fourth Edition, is focused on the development and implementation of statistically …

The dynamics of urban expansion and land use/land cover changes using remote sensing and spatial metrics: the case of Mekelle City of northern Ethiopia

AA Fenta, H Yasuda, N Haregeweyn… - … journal of remote …, 2017‏ - Taylor & Francis
Information on the rate and pattern of urban expansion is required by urban planners to
devise proper urban planning and management policy directions. This study evaluated the …