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Characterizing spatial variability in coastal wetland biomass across multiple scales using UAV and satellite imagery

Remote Sensing in Ecology and Conservation, 2021
Coastal wetland biomass is an important indicator of wetland productivity, carbon storage, health, and vulnerability to climate change. The ability to estimate aboveground biomass (AGB) in wetlands at ecologically relevant scales is complicated by the ...
Cheryl L. Doughty   +3 more
semanticscholar   +1 more source

Unsupervised Denoising for Satellite Imagery Using Wavelet Directional CycleGAN

IEEE Transactions on Geoscience and Remote Sensing, 2021
Multispectral satellite imaging sensors acquire various spectral band images and have a unique spectroscopic property in each band. Unfortunately, image artifacts from imaging sensor noise often affect the quality of scenes and have a negative impact on ...
Joonyoung Song   +5 more
semanticscholar   +1 more source

Using Satellite Imagery and Machine Learning to Estimate the Livelihood Impact of Electricity Access

Social Science Research Network, 2021
In many regions of the world, sparse data on key economic outcomes inhibits the development, targeting, and evaluation of public policy. We demonstrate how advancements in satellite imagery and machine learning can help ameliorate these data and ...
Nathan Ratledge   +4 more
semanticscholar   +1 more source

Satellite imagery acquisition planning

2015 Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics), 2015
The Agriculture sector became a high-technology industry in Turkey. The growth in agriculture has been monitoring with the help of Geographical Information Systems and Remote Sensing Technologies in last years.
Hakan Erden, Eda Camasircioglu
openaire   +1 more source

D-LinkNet: LinkNet with Pretrained Encoder and Dilated Convolution for High Resolution Satellite Imagery Road Extraction

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018
Road extraction is a fundamental task in the field of remote sensing which has been a hot research topic in the past decade. In this paper, we propose a semantic segmentation neural network, named D-LinkNet, which adopts encoderdecoder structure, dilated
Lichen Zhou, Chuang Zhang, Ming Wu
semanticscholar   +1 more source

DeepSIM: GPS Spoofing Detection on UAVs using Satellite Imagery Matching

Asia-Pacific Computer Systems Architecture Conference, 2020
Unmanned Aerial Vehicles (UAVs), better known as drones, have significantly advanced fields such as aerial surveillance, military reconnaissance, cadastral surveying, disaster monitoring, and delivery services.
Nian Xue   +5 more
semanticscholar   +1 more source

Normalization of satellite imagery

International Journal of Remote Sensing, 1990
Sets of Thematic Mapper (TM) imagery taken over the Washington, DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects.
HONGSUK H. KIM, GREGORY C. ELMAN
openaire   +1 more source

Satellite Imagery: A Crime?

SSRN Electronic Journal, 2009
The Internet was developed mainly as a homogenous, open architecture so as to develop on its own with time. Presently, we are observing a predictable backlash to the ‘corporatization’ of the network (satellite imagery), where the tools of destruction can easily be placed in the hands of the dissatisfied or malevolent people (terrorists for our context).
openaire   +1 more source

Project: Satellite Imagery

2019
In this chapter, we’ll use a software-defined radio to receive image data from NOAA weather satellites flying overhead and then render this data into a real image. Your newfound knowledge of radio theory will be plenty sufficient for you to understand what’s happening behind the scenes.
openaire   +1 more source

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