A review of remote sensing image fusion methods
H Ghassemian - Information Fusion, 2016 - Elsevier
The recent years have been marked by continuous improvements of remote sensors with
applications like monitoring and management of the environment, precision agriculture …
applications like monitoring and management of the environment, precision agriculture …
Support vector machines in remote sensing: A review
A wide range of methods for analysis of airborne-and satellite-derived imagery continues to
be proposed and assessed. In this paper, we review remote sensing implementations of …
be proposed and assessed. In this paper, we review remote sensing implementations of …
Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using Sentinel-2 imagery
P Thanh Noi, M Kappas - Sensors, 2017 - mdpi.com
In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
[HTML][HTML] Application of machine learning approaches for land cover monitoring in northern Cameroon
Abstract Machine learning (ML) models are a leading analytical technique used to monitor,
map and quantify land use and land cover (LULC) and its change over time. Models such as …
map and quantify land use and land cover (LULC) and its change over time. Models such as …
Finer resolution observation and monitoring of global land cover: First map** results with Landsat TM and ETM+ data
We have produced the first 30 m resolution global land-cover maps using Landsat Thematic
Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data. We have classified over …
Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data. We have classified over …
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 …
Using the 500 m MODIS land cover product to derive a consistent continental scale 30 m Landsat land cover classification
Classification is a fundamental process in remote sensing used to relate pixel values to land
cover classes present on the surface. Over large areas land cover classification is …
cover classes present on the surface. Over large areas land cover classification is …
[HTML][HTML] 10 m crop type map** using Sentinel-2 reflectance and 30 m cropland data layer product
The 30 m resolution US Department of Agriculture (USDA) crop data layer (CDL) is a widely
used crop type map for agricultural management and assessment, environmental impact …
used crop type map for agricultural management and assessment, environmental impact …
Monitoring land cover change in urban and peri-urban areas using dense time stacks of Landsat satellite data and a data mining approach
A Schneider - Remote Sensing of Environment, 2012 - Elsevier
Given the pace and scale of urban expansion in many parts of the globe, urban
environments are playing an increasingly important role in daily quality-of-life issues …
environments are playing an increasingly important role in daily quality-of-life issues …
Patterns and drivers of post-socialist farmland abandonment in Western Ukraine
Farmland abandonment restructures rural landscapes in many regions worldwide in
response to gradual industrialization and urbanization. In contrast, the political breakdown in …
response to gradual industrialization and urbanization. In contrast, the political breakdown in …