A survey of image classification methods and techniques for improving classification performance
Image classification is a complex process that may be affected by many factors. This paper
examines current practices, problems, and prospects of image classification. The emphasis …
examines current practices, problems, and prospects of image classification. The emphasis …
Change detection techniques based on multispectral images for investigating land cover dynamics
Satellite images provide an accurate, continuous, and synoptic view of seamless global
extent. Within the fields of remote sensing and image processing, land surface change …
extent. Within the fields of remote sensing and image processing, land surface change …
Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance
The tasselled cap transformation (TCT) is a useful tool for compressing spectral data into a
few bands associated with physical scene characteristics with minimal information loss. TCT …
few bands associated with physical scene characteristics with minimal information loss. TCT …
An assessment of the effectiveness of a random forest classifier for land-cover classification
Land cover monitoring using remotely sensed data requires robust classification methods
which allow for the accurate map** of complex land cover and land use categories …
which allow for the accurate map** of complex land cover and land use categories …
Opening the archive: How free data has enabled the science and monitoring promise of Landsat
Landsat occupies a unique position in the constellation of civilian earth observation
satellites, with a long and rich scientific and applications heritage. With nearly 40years of …
satellites, with a long and rich scientific and applications heritage. With nearly 40years of …
Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector …
Map** of patterns and spatial distribution of land-use/cover (LULC) has long been based
on remotely sensed data. In the recent past, efforts to improve the reliability of LULC maps …
on remotely sensed data. In the recent past, efforts to improve the reliability of LULC maps …
Random Forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture
VF Rodriguez-Galiano, M Chica-Olmo… - Remote Sensing of …, 2012 - Elsevier
A Random Forest (RF) classifier was applied to spectral as well as mono-and multi-seasonal
textural features extracted from Landsat TM imagery to increase the accuracy of land cover …
textural features extracted from Landsat TM imagery to increase the accuracy of land cover …
Object-based crop identification using multiple vegetation indices, textural features and crop phenology
Crop identification on specific parcels and the assessment of soil management practices are
important for agro-ecological studies, greenhouse gas modeling, and agrarian policy …
important for agro-ecological studies, greenhouse gas modeling, and agrarian policy …
Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing
The importance of accurate and timely information describing the nature and extent of land
resources and changes over time is increasing, especially in rapidly growing metropolitan …
resources and changes over time is increasing, especially in rapidly growing metropolitan …
Crop classification of upland fields using Random forest of time-series Landsat 7 ETM+ data
Crop classification of homogeneous landscapes and phenology is a common requirement to
estimate land cover map**, monitoring, and land use categories accurately. In recent …
estimate land cover map**, monitoring, and land use categories accurately. In recent …