Current and future applications of statistical machine learning algorithms for agricultural machine vision systems
With being rapid increasing population in worldwide, the need for satisfactory level of crop
production with decreased amount of agricultural lands. Machine vision would ensure the …
production with decreased amount of agricultural lands. Machine vision would ensure the …
Developments in Landsat land cover classification methods: A review
D Phiri, J Morgenroth - Remote Sensing, 2017 - mdpi.com
Land cover classification of Landsat images is one of the most important applications
developed from Earth observation satellites. The last four decades were marked by different …
developed from Earth observation satellites. The last four decades were marked by different …
Optical remote sensing image change detection based on attention mechanism and image difference
X Peng, R Zhong, Z Li, Q Li - IEEE Transactions on Geoscience …, 2020 - ieeexplore.ieee.org
This study presents a new end-to-end change detection network, called difference-
enhancement dense-attention convolutional neural network (DDCNN), that is designed for …
enhancement dense-attention convolutional neural network (DDCNN), that is designed for …
[HTML][HTML] Global land cover mapping at 30 m resolution: A POK-based operational approach
Abstract Global Land Cover (GLC) information is fundamental for environmental change
studies, land resource management, sustainable development, and many other societal …
studies, land resource management, sustainable development, and many other societal …
The first wetland inventory map of newfoundland at a spatial resolution of 10 m using sentinel-1 and sentinel-2 data on the google earth engine cloud computing …
Wetlands are one of the most important ecosystems that provide a desirable habitat for a
great variety of flora and fauna. Wetland mapping and modeling using Earth Observation …
great variety of flora and fauna. Wetland mapping and modeling using Earth Observation …
Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 data on Google Earth …
J Xiong, PS Thenkabail, JC Tilton, MK Gumma… - Remote Sensing, 2017 - mdpi.com
A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must
for food and water security analysis. Precise and accurate global cropland extent maps …
for food and water security analysis. Precise and accurate global cropland extent maps …
Change detection from remotely sensed images: From pixel-based to object-based approaches
M Hussain, D Chen, A Cheng, H Wei… - ISPRS Journal of …, 2013 - Elsevier
The appetite for up-to-date information about earth's surface is ever increasing, as such
information provides a base for a large number of applications, including local, regional and …
information provides a base for a large number of applications, including local, regional and …
A critical synthesis of remotely sensed optical image change detection techniques
State of the art reviews of remote sensing change detection are becoming increasingly
complicated and disparate due to an ever growing list of techniques, algorithms and …
complicated and disparate due to an ever growing list of techniques, algorithms and …
A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT …
Pixel-based and object-based image analysis approaches for classifying broad land cover
classes over agricultural landscapes are compared using three supervised machine …
classes over agricultural landscapes are compared using three supervised machine …
Detecting the boundaries of urban areas in india: A dataset for pixel-based image classification in google earth engine
Urbanization often occurs in an unplanned and uneven manner, resulting in profound
changes in patterns of land cover and land use. Understanding these changes is …
changes in patterns of land cover and land use. Understanding these changes is …