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Data-and knowledge-driven mineral prospectivity maps for Canada's North
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 …
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
This study evaluates and compares the performance of four machine learning classifiers—
support vector machine (SVM), normal Bayes (NB), classification and regression tree …
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
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 …
are rarely tested with the same classification task. In this research, with the same Landsat …
Feature selection for classification of hyperspectral data by SVM
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 …
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
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 …
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
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 …
land use/land cover (LULC) datasets at regional to global scales to support a variety of …
Assessing the accuracy of blending Landsat–MODIS surface reflectances in two landscapes with contrasting spatial and temporal dynamics: A framework for algorithm …
Blending algorithms model land cover change by using highly resolved spatial data from
one sensor and highly resolved temporal data from another. Because the data are not …
one sensor and highly resolved temporal data from another. Because the data are not …
[HTML][HTML] Feature selection of time series MODIS data for early crop classification using random forest: A case study in Kansas, USA
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 …
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 …
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
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 …
devise proper urban planning and management policy directions. This study evaluated the …