Land surface data is one of the entry points for a enormous resource management and
human activity such as to monitor farming, ecology, urban management, and territories. This …

Land-use mapping and crop classification have both benefited greatly from the analysis of
high-resolution remote sensing photos based on deep learning. This research proposes …

As the landscapes changes day by day it leads to the increasing use of unused lands, by
which unused lands can be used for various purposes like agriculture, developing city …

In satellite image analysis, classification of objects appearing in an image is a major step of
information extraction. The information acquired from the satellite image can be used to …

Background: Deep Learning (DL) neural network methods have become a hotspot subject of
research in the remote sensing field. Classification of aerial satellite images depends on …

Over the last decade, remote sensing technology has advanced dramatically, resulting in
significant improvements on image quality, data volume, and application usage. These …

In this work, we are creating a system to classify satellite images in order to extract
information using image processing techniques. Classification of satellite images into used …

Ecology is the scientific study of balancing biodiversity, which has an impact on natural life
and habitats and establishes a strong yet complicated link between the ecosystem's …

Land cover classification is a vital task in remote sensing to emerging demands in global
and echo-friendly environmental applications. This type of analysis will empower with …

Deep learning convolutional neural network (CNN) is popular as being widely used for
classification of unstructured data. Land use land cover (LULC) classification using remote …