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gnss: rename JPL-SIDESHOW to SIDESHOW (#1240)
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+ utils.arg_utils.add_gnss_argument(): rename --gnss-source JPL-SIDESHOW to SIDESHOW for simplicity

+ objects.gnss: use "SIDESHOW" instead of "JPL-SIDESHOW" or "JPL_SIDESHOW" for all variable names and values

+ objects.gnss: add reference info in the code comments for GNSS_UNR/SIDESHOW, did not find citation/reference info for GNSS_ESESES, thus, did not add it yet.

+ docs.references.md: update to reflect the current references noted in the smallbaselineApp.cfg file.

Unrelated changes:

+ utils.network.simulate_coherence(): convert SNR from dB to 1 for thermal decorrelation

+ README: fix broken link
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2 changes: 1 addition & 1 deletion docs/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -112,4 +112,4 @@ _This disclaimer was adapted from the [MetPy project](https://github.com/Unidata

Yunjun, Z., Fattahi, H., and Amelung, F. (2019), Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction, _Computers & Geosciences_, _133_, 104331. [ [doi](https://doi.org/10.1016/j.cageo.2019.104331) \| [arxiv](https://doi.org/10.31223/osf.io/9sz6m) \| [data](https://doi.org/10.5281/zenodo.3464190) \| [notebook](https://github.com/geodesymiami/Yunjun_et_al-2019-MintPy) ]

In addition to the above, we recommend that you cite the original publications that describe the algorithms used in your specific analysis. They are noted briefly in the [default template file](../mintpy/defaults/smallbaselineApp.cfg) and listed in the [references.md file](./references.md).
In addition to the above, we recommend that you cite the original publications that describe the algorithms used in your specific analysis. They are noted briefly in the [default template file](../src/mintpy/defaults/smallbaselineApp.cfg) and listed in the [reference file](./references.md).
68 changes: 45 additions & 23 deletions docs/references.md
Original file line number Diff line number Diff line change
@@ -1,45 +1,67 @@
## Revalent Scientific Papers
## Revalent Literature

+ Berardino, P., G. Fornaro, R. Lanari, and E. Sansosti (2002), A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms, _Geoscience and Remote Sensing, IEEE Transactions on, 40_(11), 2375-2383, doi:10.1109/TGRS.2002.803792.
+ Berardino, P., Fornaro, G., Lanari, R., & Sansosti, E. (2002). A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. _IEEE Transactions on Geoscience and Remote Sensing, 40_(11), 2375-2383. doi:[10.1109/TGRS.2002.803792](https://doi.org/10.1109/TGRS.2002.803792)

+ Chaussard, E., F. Amelung, and Y. Aoki (2013), Characterization of open and closed volcanic systems in Indonesia and Mexico using InSAR time series, _Journal of Geophysical Research: Solid Earth, 118_(8), 3957-3969, doi:10.1002/jgrb.50288.
+ Blewitt, G., Hammond, W., & Kreemer, C. (2018). Harnessing the GPS data explosion for interdisciplinary science. _Eos, 99_. doi:[10.1029/2018EO104623](https://doi.org/10.1029/2018EO104623)

+ Chaussard, E., R. Bürgmann, H. Fattahi, R. M. Nadeau, T. Taira, C. W. Johnson, and I. Johanson (2015), Potential for larger earthquakes in the East San Francisco Bay Area due to the direct connection between the Hayward and Calaveras Faults, _Geophysical Research Letters, 42_(8), 2734-2741, doi:10.1002/2015GL063575.
+ Chaussard, E., Amelung, F., & Aoki, Y. (2013). Characterization of open and closed volcanic systems in Indonesia and Mexico using InSAR time series. _Journal of Geophysical Research: Solid Earth, 118_(8), 3957-3969. doi:[10.1002/jgrb.50288](https://doi.org/10.1002/jgrb.50288)

+ Chen, C. W., and H. A. Zebker (2001), Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization, _JOSA A, 18_(2), 338-351, doi:10.1364/JOSAA.18.000338.
+ Chaussard, E., Bürgmann, R., Fattahi, H., Nadeau, R. M., Taira, T., Johnson, C. W., & Johanson, I. (2015). Potential for larger earthquakes in the East San Francisco Bay Area due to the direct connection between the Hayward and Calaveras Faults. _Geophysical Research Letters, 42_(8), 2734-2741. doi:[10.1002/2015GL063575](https://doi.org/10.1002/2015GL063575)

+ Doin, M. P., C. Lasserre, G. Peltzer, O. Cavalié, and C. Doubre (2009), Corrections of stratified tropospheric delays in SAR interferometry: Validation with global atmospheric models, _Journal of Applied Geophysics, 69_(1), 35-50, doi:10.1016/j.jappgeo.2009.03.010.
+ Chen, C. W., & Zebker, H. A. (2001). Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization. _Journal of the Optical Society of America A, 18_(2), 338-351. doi:[10.1364/JOSAA.18.000338](https://doi.org/10.1364/JOSAA.18.000338)

+ Fattahi, H., and F. Amelung (2013), DEM Error Correction in InSAR Time Series, _Geoscience and Remote Sensing, IEEE Transactions on, 51_(7), 4249-4259, doi:10.1109/TGRS.2012.2227761.
+ Doin, M. P., Lasserre, C., Peltzer, G., Cavalié, O., & Doubre, C. (2009). Corrections of stratified tropospheric delays in SAR interferometry: Validation with global atmospheric models. _Journal of Applied Geophysics, 69_(1), 35-50. doi:[10.1016/j.jappgeo.2009.03.010](https://doi.org/10.1016/j.jappgeo.2009.03.010)

+ Fattahi, H., and F. Amelung (2015), InSAR bias and uncertainty due to the systematic and stochastic tropospheric delay, _Journal of Geophysical Research: Solid Earth, 120_(12), 8758-8773, doi:10.1002/2015JB012419.
+ Efron, B., & Tibshirani, R. (1986). Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy. _Statistical science_, 54-75. doi:[10.1214/ss/1177013815](https://doi.org/10.1214/ss/1177013815)

+ Fattahi, H., P. Agram, and M. Simons (2016), A Network-Based Enhanced Spectral Diversity Approach for TOPS Time-Series Analysis, _IEEE Transactions on Geoscience and Remote Sensing, 55_(2), 777-786, doi:10.1109/TGRS.2016.2614925.
+ Fattahi, H., & Amelung, F. (2013). DEM Error Correction in InSAR Time Series. _IEEE Transactions on Geoscience and Remote Sensing, 51_(7), 4249-4259. doi:[10.1109/TGRS.2012.2227761](https://doi.org/10.1109/TGRS.2012.2227761)

+ Jolivet, R., R. Grandin, C. Lasserre, M. P. Doin, and G. Peltzer (2011), Systematic InSAR tropospheric phase delay corrections from global meteorological reanalysis data, _Geophysical Research Letters, 38_(17), L17311, doi:10.1029/2011GL048757.
+ Fattahi, H., & Amelung, F. (2015). InSAR bias and uncertainty due to the systematic and stochastic tropospheric delay. _Journal of Geophysical Research: Solid Earth, 120_(12), 8758-8773. doi:[10.1002/2015JB012419](https://doi.org/10.1002/2015JB012419)

+ Jolivet, R., P. S. Agram, N. Y. Lin, M. Simons, M. P. Doin, G. Peltzer, and Z. Li (2014), Improving InSAR geodesy using global atmospheric models, _Journal of Geophysical Research: Solid Earth, 119_(3), 2324-2341, doi:10.1002/2013JB010588.
+ Fattahi, H., Agram, P., & Simons, M. (2016). A Network-Based Enhanced Spectral Diversity Approach for TOPS Time-Series Analysis. _IEEE Transactions on Geoscience and Remote Sensing, 55_(2), 777-786. doi:[10.1109/TGRS.2016.2614925](https://doi.org/10.1109/TGRS.2016.2614925)

+ Marinkovic, P., and Y. Larsen (2013), Consequences of long-term ASAR local oscillator frequency decay - An empirical study of 10 years of data, paper presented at _Proceedings of the Living Planet Symposium_ (abstract), European Space Agency, Edinburgh, U. K.
+ Fattahi, H., Simons, M., & Agram, P. (2017). InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique. _IEEE Transactions on Geoscience and Remote Sensing, 55_(10), 5984-5996. doi:[10.1109/TGRS.2017.2718566](https://doi.org/10.1109/TGRS.2017.2718566)

+ Morales Rivera, A. M., F. Amelung, and P. Mothes (2016), Volcano Deformation Survey over the Northern and Central Andes with ALOS InSAR Time Series, _Geochemistry, Geophysics, Geosystems_, 17, 2869-2883, doi:10.1002/2016GC006393.
+ Gomba, G., Parizzi, A., Zan, F. D., Eineder, M., & Bamler, R. (2016). Toward Operational Compensation of Ionospheric Effects in SAR Interferograms: The Split-Spectrum Method. _IEEE Transactions on Geoscience and Remote Sensing, 54_(3), 1446-1461. doi:[10.1109/TGRS.2015.2481079](https://doi.org/10.1109/TGRS.2015.2481079)

+ Pepe, A., and R. Lanari (2006), On the extension of the minimum cost flow algorithm for phase unwrapping of multitemporal differential SAR interferograms, _Geoscience and Remote Sensing, IEEE Transactions on, 44_(9), 2374-2383, doi:10.1109/TGRS.2006.873207.
+ Heflin, M., Donnellan, A., Parker, J., Lyzenga, G., Moore, A., Ludwig, L. G., et al. (2020). Automated Estimation and Tools to Extract Positions, Velocities, Breaks, and Seasonal Terms From Daily GNSS Measurements: Illuminating Nonlinear Salton Trough Deformation. _Earth and Space Scien10.1029/2011JB008731ce, 7_(7), e2019EA000644, doi:[10.1029/2019EA000644](https://doi.org/10.1029/2019EA000644)

+ Perissin, D., and T. Wang (2012), Repeat-pass SAR interferometry with partially coherent targets, _Geoscience and Remote Sensing, IEEE Transactions on, 50_(1), 271-280, doi:10.1109/tgrs.2011.2160644.
+ Hetland, E., Musé, P., Simons, M., Lin, Y., Agram, P., & DiCaprio, C. (2012). Multiscale InSAR time series (MInTS) analysis of surface deformation. _Journal of Geophysical Research: Solid Earth, 117_(B2). doi:[10.1029/2011JB008731](https://doi.org/10.1029/2011JB008731)

+ Rosen, P. A., S. Hensley, G. Peltzer, and M. Simons (2004), Updated repeat orbit interferometry package released, _Eos Trans. AGU, 85_(5), 47-47, doi:10.1029/2004EO050004.
+ Jolivet, R., Grandin, R., Lasserre, C., Doin, M. P., & Peltzer, G. (2011). Systematic InSAR tropospheric phase delay corrections from global meteorological reanalysis data. _Geophysical Research Letters, 38_(17), L17311. doi:[10.1029/2011GL048757](https://doi.org/10.1029/2011GL048757)

+ Rosen, P. A., E. Gurrola, G. F. Sacco, and H. Zebker (2012), The InSAR scientific computing environment, paper presented at _EUSAR 2012_, 23-26 April 2012.
+ Jolivet, R., Agram, P. S., Lin, N. Y., Simons, M., Doin, M. P., Peltzer, G., & Li, Z. (2014). Improving InSAR geodesy using global atmospheric models. _Journal of Geophysical Research: Solid Earth, 119_(3), 2324-2341. doi:[10.1002/2013JB010588](https://doi.org/10.1002/2013JB010588)

+ Tough, R. J. A., D. Blacknell, and S. Quegan (1995), A Statistical Description of Polarimetric and Interferometric Synthetic Aperture Radar Data, _Proceedings: Mathematical and Physical Sciences, 449_(1937), 567-589, doi:10.1098/rspa.1995.0059.
+ Kang, Y., Lu, Z., Zhao, C., Xu, Y., Kim, J.-w., & Gallegos, A. J. (2021). InSAR monitoring of creeping landslides in mountainous regions: A case study in Eldorado National Forest, California. _Remote Sensing of Environment, 258_, 112400. doi:[10.1016/j.rse.2021.112400](https://doi.org/10.1016/j.rse.2021.112400)

+ Werner, C., U. Wegmüller, T. Strozzi, and A. Wiesmann (2000), Gamma SAR and interferometric processing software, paper presented at _Proceedings of the ERS-Envisat symposium_, Gothenburg, Sweden.
+ Liang, C., Liu, Z., Fielding, E. J., & Bürgmann, R. (2018). InSAR Time Series Analysis of L-Band Wide-Swath SAR Data Acquired by ALOS-2. _IEEE Transactions on Geoscience and Remote Sensing, 56_(8), 4492-4506. doi:[10.1109/TGRS.2018.2821150](https://doi.org/10.1109/TGRS.2018.2821150)

+ Yu, C., Z. Li, and N. T. Penna (2018), Interferometric synthetic aperture radar atmospheric correction using a GPS-based iterative tropospheric decomposition model, Remote Sensing of Environment, 204, 109-121, doi:10.1016/j.rse.2017.10.038.
+ Liang, C., Agram, P., Simons, M., & Fielding, E. J. (2019). Ionospheric Correction of InSAR Time Series Analysis of C-band Sentinel-1 TOPS Data. _IEEE Transactions on Geoscience and Remote Sensing, 59_(9), 6755 - 6773. doi:[10.1109/TGRS.2019.2908494](https://doi.org/10.1109/TGRS.2019.2908494)

+ Yu, C., Z. Li, N. T. Penna, and P. Crippa (2018), Generic Atmospheric Correction Model for Interferometric Synthetic Aperture Radar Observations, Journal of Geophysical Research: Solid Earth, 123(10), 9202-9222, doi:10.1029/2017JB015305.
+ Marinkovic, P., & Larsen, Y. (2013). Consequences of long-term ASAR local oscillator frequency decay - An empirical study of 10 years of data. Paper presented at _Proceedings of the Living Planet Symposium_ (abstract), European Space Agency, Edinburgh, UK.

+ Yunjun, Z., H. Fattahi, and F. Amelung (2019), Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction, _Computers & Geosciences, 133_, 104331, doi:10.1016/j.cageo.2019.104331.
+ Milbert, D. (2018), "solid: Solid Earth Tide", [Online]. Available: http://geodesyworld.github.io/SOFTS/solid.htm. Accessd on: 2020-09-06.

+ Zebker, H. A., P. A. Rosen, and S. Hensley (1997), Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps, _Journal of Geophysical Research: Solid Earth, 102_(B4), 7547-7563, doi:10.1029/96JB03804.
+ Morales Rivera, A. M., Amelung, F., & Mothes, P. (2016). Volcano Deformation Survey over the Northern and Central Andes with ALOS InSAR Time Series. _Geochemistry, Geophysics, Geosystems, 17_, 2869-2883. doi:[10.1002/2016GC006393](https://doi.org/10.1002/2016GC006393)

+ Pepe, A., & Lanari, R. (2006). On the extension of the minimum cost flow algorithm for phase unwrapping of multitemporal differential SAR interferograms. _IEEE Transactions on Geoscience and Remote Sensing, 44_(9), 2374-2383. doi:[10.1109/TGRS.2006.873207](https://doi.org/10.1109/TGRS.2006.873207)

+ Perissin, D., & Wang, T. (2012). Repeat-pass SAR interferometry with partially coherent targets. _IEEE Transactions on Geoscience and Remote Sensing, 50_(1), 271-280. doi:[10.1109/tgrs.2011.2160644](https://doi.org/10.1109/tgrs.2011.2160644)

+ Rosen, P. A., Hensley, S., Peltzer, G., & Simons, M. (2004). Updated repeat orbit interferometry package released. _Eos Trans. AGU, 85_(5), 47-47. doi:[10.1029/2004EO050004](https://doi.org/10.1029/2004EO050004)

+ Rosen, P. A., Gurrola, E., Sacco, G. F. & Zebker, H. (2012). The InSAR scientific computing environment. Paper presented at _EUSAR 2012_, Nuremberg, Germany.

+ Seymour, M. S., & Cumming, I. G. (1994). Maximum likelihood estimation for SAR interferometry. Paper presented at the _Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium_. doi:[10.1109/IGARSS.1994.399711](https://doi.org/10.1109/IGARSS.1994.399711)

+ Tough, R. J. A., Blacknell, D., & Quegan, S. (1995). A Statistical Description of Polarimetric and Interferometric Synthetic Aperture Radar Data. _Proceedings: Mathematical and Physical Sciences, 449_(1937), 567-589. doi:[10.1098/rspa.1995.0059](https://doi.org/10.1098/rspa.1995.0059)

+ Werner, C., Wegmüller, U., Strozzi, T., & Wiesmann, A. (2000). Gamma SAR and interferometric processing software. Paper presented at the _Proceedings of the ERS-Envisat symposium_, Gothenburg, Sweden.

+ Yu, C., Li, Z., Penna, N. T., & Crippa, P. (2018). Generic Atmospheric Correction Model for Interferometric Synthetic Aperture Radar Observations. _Journal of Geophysical Research: Solid Earth, 123_(10), 9202-9222. doi:[10.1029/2017JB015305](https://doi.org/10.1029/2017JB015305)

+ Yunjun, Z., Fattahi, H., & Amelung, F. (2019). Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction. _Computers & Geosciences, 133_, 104331. doi:[10.1016/j.cageo.2019.104331](https://doi.org/10.1016/j.cageo.2019.104331)

+ Yunjun, Z., Fattahi, H., Pi, X., Rosen, P., Simons, M., Agram, P., & Aoki, Y. (2022). Range Geolocation Accuracy of C-/L-Band SAR and its Implications for Operational Stack Coregistration. IEEE Transactions on Geoscience and Remote Sensing, 60, 5227219. doi:[10.1109/TGRS.2022.3168509](https://doi.org/10.1109/TGRS.2022.3168509)

+ Zebker, H. A., Rosen, P. A., & Hensley, S. (1997). Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps. _Journal of Geophysical Research: Solid Earth, 102_(B4), 7547-7563. doi:[10.1029/96JB03804](https://doi.org/10.1029/96JB03804)
43 changes: 28 additions & 15 deletions src/mintpy/objects/gnss.py
Original file line number Diff line number Diff line change
Expand Up @@ -21,10 +21,10 @@
from mintpy.utils import ptime, readfile, time_func, utils1 as ut

GNSS_SITE_LIST_URLS = {
'UNR' : 'http://geodesy.unr.edu/NGLStationPages/DataHoldings.txt',
'ESESES' : 'http://garner.ucsd.edu/pub/measuresESESES_products/Velocities/ESESES_Velocities.txt',
'JPL-SIDESHOW' : 'https://sideshow.jpl.nasa.gov/post/tables/table2.html',
'GENERIC' : None,
'UNR' : 'http://geodesy.unr.edu/NGLStationPages/DataHoldings.txt',
'ESESES' : 'http://garner.ucsd.edu/pub/measuresESESES_products/Velocities/ESESES_Velocities.txt',
'SIDESHOW' : 'https://sideshow.jpl.nasa.gov/post/tables/table2.html',
'GENERIC' : None,
}
GNSS_SOURCES = list(GNSS_SITE_LIST_URLS.keys())

Expand Down Expand Up @@ -64,8 +64,8 @@ def search_gnss(SNWE, start_date=None, end_date=None, source='UNR', site_list_fi
sites = read_UNR_site_list(site_list_file)
elif source == 'ESESES':
sites = read_ESESES_site_list(site_list_file)
elif source == 'JPL-SIDESHOW':
sites = read_JPL_SIDESHOW_site_list(site_list_file)
elif source == 'SIDESHOW':
sites = read_SIDESHOW_site_list(site_list_file)
elif source == 'GENERIC':
sites = read_GENERIC_site_list(site_list_file)

Expand Down Expand Up @@ -143,7 +143,7 @@ def read_UNR_site_list(site_list_file:str):


def read_ESESES_site_list(site_list_file:str):
"""Return names and lon/lat values for JPL GNSS stations.
"""Return names and lon/lat values for JPL/SOPAC ESESES GNSS stations.
"""
fc = np.loadtxt(site_list_file, skiprows=17, dtype=str)
sites = {
Expand All @@ -154,8 +154,8 @@ def read_ESESES_site_list(site_list_file:str):
return sites


def read_JPL_SIDESHOW_site_list(site_list_file:str):
"""Return names and lon/lat values for JPL-SIDESHOW GNSS stations.
def read_SIDESHOW_site_list(site_list_file:str):
"""Return names and lon/lat values for JPL SIDESHOW GNSS stations.
"""
fc = np.loadtxt(site_list_file, comments='<', skiprows=9, dtype=str)
sites = {
Expand Down Expand Up @@ -348,8 +348,8 @@ def get_gnss_class(source:str):
return GNSS_UNR
elif source == 'ESESES':
return GNSS_ESESES
elif source == 'JPL-SIDESHOW':
return GNSS_JPL_SIDESHOW
elif source == 'SIDESHOW':
return GNSS_SIDESHOW
elif source == 'GENERIC':
return GNSS_GENERIC
else:
Expand Down Expand Up @@ -791,6 +791,11 @@ class GNSS_UNR(GNSS):
at University of Nevada, Reno (UNR).
Website: http://geodesy.unr.edu/NGLStationPages/GlobalStationList
Reference:
Blewitt, G., Hammond, W., & Kreemer, C. (2018). Harnessing the GPS data
explosion for interdisciplinary science. Eos, 99. doi:10.1029/2018EO104623
"""
def __init__(self, site: str, data_dir=None, version='IGS14', url_prefix=None):
super().__init__(
Expand Down Expand Up @@ -1037,17 +1042,25 @@ def read_displacement(self, start_date=None, end_date=None, print_msg=True, disp
self.std_e, self.std_n, self.std_u)


class GNSS_JPL_SIDESHOW(GNSS):
"""GNSS class for daily solutions processed by JPL-SIDESHOW.
class GNSS_SIDESHOW(GNSS):
"""GNSS class for daily solutions processed by JPL SIDESHOW,
funded by NASA's Space Geodesy Task.
Website: https://sideshow.jpl.nasa.gov/pub/
https://sideshow.jpl.nasa.gov/post/series.html
Reference:
Heflin, M., Donnellan, A., Parker, J., Lyzenga, G., Moore, A., Ludwig, L. G., et al.
(2020). Automated Estimation and Tools to Extract Positions, Velocities, Breaks, and
Seasonal Terms From Daily GNSS Measurements: Illuminating Nonlinear Salton Trough
Deformation. Earth and Space Science, 7(7), e2019EA000644, doi:10.1029/2019EA000644
"""
def __init__(self, site: str, data_dir=None, version='IGS14', url_prefix=None):
super().__init__(
site=site,
data_dir=data_dir,
version=version,
source='JPL-SIDESHOW',
source='SIDESHOW',
url_prefix=url_prefix,
)

Expand All @@ -1068,7 +1081,7 @@ def get_site_lat_lon(self, print_msg=False) -> (float, float):
Returns: self.lat/lon - float
"""
# need to refer to the site list
site_list_file = os.path.basename(GNSS_SITE_LIST_URLS['JPL-SIDESHOW'])
site_list_file = os.path.basename(GNSS_SITE_LIST_URLS['SIDESHOW'])

# find site in site list file
with open(site_list_file) as site_list:
Expand Down
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