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references.bib
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@incollection{SCHOWENGERDT2007285,
title = {CHAPTER 7 - Correction and Calibration},
editor = {Robert A. Schowengerdt},
booktitle = {Remote Sensing (Third Edition)},
publisher = {Academic Press},
edition = {Third Edition},
address = {Burlington},
pages = {285-XXIII},
year = {2007},
isbn = {978-0-12-369407-2},
doi = {https://doi.org/10.1016/B978-012369407-2/50010-3},
url = {https://www.sciencedirect.com/science/article/pii/B9780123694072500103},
author = {Robert A. Schowengerdt},
abstract = {Publisher Summary
Remote-sensing images require various types of systematic corrections for noise and geometric distortion. They also require radiometric calibration for accurate comparisons between dates and sensors. Rectification of system-corrected products to maps can be implemented over limited areas with moderate topographic relief by global polynomial functions. Resampling for geometric correction alters the local spatial and global radiometric properties of the image. Nearest-neighbor resampling does not introduce any new pixel spectral vectors into the data, bilinear resampling introduces new vectors within the original digital number (DN) range, and cubic resampling introduces new vectors within and outside the original DN range. Noise correction is necessary only if the noise will affect information extraction. It is best done before any resampling of the imagery. Local noise is removed with a variety of spatial filters, while global periodic noise is removed with Fourier filters. Unequal detector calibration noise or striping can be corrected by a global image-based adjustment of each detector's response. Uncorrelated noise in multispectral images may be removed by spectral decorrelation techniques such as the principal component transfer (PCT). Full calibration of remote sensing imagery requires sensor calibration and atmospheric and topographic effects correction. Hyperspectral imagery presents special calibration challenges but also provides some atmospheric data that is useful for calibration.}
}
@article{chen2020hydrological,
title={Hydrological basis of the Budyko curve: Data-guided exploration of the mediating role of soil moisture},
author={Chen, Xi and Sivapalan, Murugesu},
journal={Water Resources Research},
volume={56},
number={10},
pages={e2020WR028221},
year={2020},
publisher={Wiley Online Library}
}
@article{nash1999world,
title={World atlas of desertification},
author={Nash, David J},
journal={The Geographical Journal},
volume={165},
pages={325},
year={1999},
publisher={Blackwell Publishing Ltd.}
}
@article{zomer2022version,
title={Version 3 of the global aridity index and potential evapotranspiration database},
author={Zomer, Robert J and Xu, Jianchu and Trabucco, Antonio},
journal={Scientific Data},
volume={9},
number={1},
pages={409},
year={2022},
publisher={Nature Publishing Group UK London}
}
@article{iturbide2020,
title = {An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets},
author = {Iturbide, Maialen and {Gutiérrez}, {José M.} and Alves, Lincoln M. and Bedia, {Joaquín} and Cerezo-Mota, Ruth and Cimadevilla, Ezequiel and {Cofiño}, Antonio S. and Di Luca, Alejandro and Faria, Sergio Henrique and Gorodetskaya, Irina V. and Hauser, Mathias and Herrera, Sixto and Hennessy, Kevin and Hewitt, Helene T. and Jones, Richard G. and Krakovska, Svitlana and Manzanas, Rodrigo and {Martínez-Castro}, Daniel and Narisma, Gemma T. and Nurhati, Intan S. and Pinto, Izidine and Seneviratne, Sonia I. and van den Hurk, Bart and Vera, Carolina S.},
year = {2020},
month = {11},
date = {2020-11-18},
journal = {Earth System Science Data},
pages = {2959--2970},
volume = {12},
number = {4},
doi = {10.5194/essd-12-2959-2020},
url = {http://dx.doi.org/10.5194/essd-12-2959-2020},
langid = {en}
}
@article{entekhabi2009,
title = {The Soil Moisture Active and Passive Mission (SMAP): Science and applications},
author = {Entekhabi, Dara and Njoku, Eni and {O'Neill}, Peggy},
year = {2009},
date = {2009},
journal = {2009 IEEE Radar Conference},
doi = {10.1109/radar.2009.4977030},
url = {http://dx.doi.org/10.1109/radar.2009.4977030}
}
@article{huete1999modis,
title={MODIS vegetation index (MOD13)},
author={Huete, Alfredo and Justice, Chris and Van Leeuwen, Wim},
journal={Algorithm theoretical basis document},
volume={3},
number={213},
pages={295--309},
year={1999}
}
@article{zomer2022version,
title={Version 3 of the global aridity index and potential evapotranspiration database},
author={Zomer, Robert J and Xu, Jianchu and Trabucco, Antonio},
journal={Scientific Data},
volume={9},
number={1},
pages={409},
year={2022},
publisher={Nature Publishing Group UK London}
}
@article{crameri2018geodynamic,
title={Geodynamic diagnostics, scientific visualisation and StagLab 3.0},
author={Crameri, Fabio},
journal={Geoscientific Model Development},
volume={11},
number={6},
pages={2541--2562},
year={2018},
publisher={Copernicus Publications G{\"o}ttingen, Germany}
}
@article{kovesi2015good,
title={Good colour maps: How to design them},
author={Kovesi, Peter},
journal={arXiv preprint arXiv:1509.03700},
year={2015}
}
@article{chaney2019polaris,
title={POLARIS soil properties: 30-m probabilistic maps of soil properties over the contiguous United States},
author={Chaney, Nathaniel W and Minasny, Budiman and Herman, Jonathan D and Nauman, Travis W and Brungard, Colby W and Morgan, Cristine LS and McBratney, Alexander B and Wood, Eric F and Yimam, Yohannes},
journal={Water Resources Research},
volume={55},
number={4},
pages={2916--2938},
year={2019},
publisher={Wiley Online Library}
}
@article{chaney2016polaris,
title={POLARIS: A 30-meter probabilistic soil series map of the contiguous United States},
author={Chaney, Nathaniel W and Wood, Eric F and McBratney, Alexander B and Hempel, Jonathan W and Nauman, Travis W and Brungard, Colby W and Odgers, Nathan P},
journal={Geoderma},
volume={274},
pages={54--67},
year={2016},
publisher={Elsevier}
}