Machine learning based hyperspectral image analysis: a survey
Hyperspectral sensors enable the study of the chemical properties of scene materials
remotely for the purpose of identification, detection, and chemical composition analysis of …
remotely for the purpose of identification, detection, and chemical composition analysis of …
Spatial evapotranspiration, rainfall and land use data in water accounting–Part 1: Review of the accuracy of the remote sensing data
P Karimi, WGM Bastiaanssen - Hydrology and Earth System …, 2015 - hess.copernicus.org
The scarcity of water encourages scientists to develop new analytical tools to enhance water
resource management. Water accounting and distributed hydrological models are examples …
resource management. Water accounting and distributed hydrological models are examples …
Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery
GL Feyisa, H Meilby, R Fensholt, SR Proud - Remote sensing of …, 2014 - Elsevier
Classifying surface cover types and analyzing changes are among the most common
applications of remote sensing. One of the most basic classification tasks is to distinguish …
applications of remote sensing. One of the most basic classification tasks is to distinguish …
On digital soil mapping
We review various recent approaches to making digital soil maps based on geographic
information systems (GIS) data layers, note some commonalities and propose a generic …
information systems (GIS) data layers, note some commonalities and propose a generic …
Change detection techniques
D Lu, P Mausel, E Brondizio… - International journal of …, 2004 - Taylor & Francis
Timely and accurate change detection of Earth's surface features is extremely important for
understanding relationships and interactions between human and natural phenomena in …
understanding relationships and interactions between human and natural phenomena in …
Europe-wide reduction in primary productivity caused by the heat and drought in 2003
Future climate warming is expected to enhance plant growth in temperate ecosystems and
to increase carbon sequestration,. But although severe regional heatwaves may become …
to increase carbon sequestration,. But although severe regional heatwaves may become …
Difference enhancement and spatial–spectral nonlocal network for change detection in VHR remote sensing images
The popular Siamese convolutional neural networks (CNNs) for remote sensing (RS) image
change detection (CD) often suffer from two problems. First, they either ignore the original …
change detection (CD) often suffer from two problems. First, they either ignore the original …
From W-Net to CDGAN: Bitemporal change detection via deep learning techniques
Traditional change detection methods usually follow the image differencing, change feature
extraction, and classification framework, and their performance is limited by such simple …
extraction, and classification framework, and their performance is limited by such simple …
Remote sensing image change detection based on deep multi-scale multi-attention Siamese transformer network
Change detection is a technique that can observe changes in the surface of the earth
dynamically. It is one of the most significant tasks in remote sensing image processing. In the …
dynamically. It is one of the most significant tasks in remote sensing image processing. In the …
Climate change can cause spatial mismatch of trophically interacting species
Climate change is one of the most influential drivers of biodiversity. Species‐specific
differences in the reaction to climate change can become particularly important when …
differences in the reaction to climate change can become particularly important when …