2023
Wang, Ran; Springer, K.R; Gamon, J.A. Confounding effects of snow cover on remotely sensed vegetation indices of evergreen and deciduous trees: An experimental study. Global Change Biology. 2023, 29.21, 6120. https://doi.org/10.1111/gcb.16916
2021
Zeng, L.; Wardlow, B.D.; Hu, S.; Zhang, X.; Zhou, G.; Peng, G.; Xiang, D.; Wang, R.; Meng, R.; Wu, W. A Novel Strategy to Reconstruct NDVI Time-Series with High Temporal Resolution from MODIS Multi-Temporal Composite Products. Remote Sens. 2021, 13, 1397. https://doi.org/10.3390/rs13071397
2019
Fernández-Martínez, M.; Yu, R.; Gamon, J.; Hmimina, G.; Filella, I.; Balzarolo, M.; Stocker, B.; Peñuelas, J. Monitoring Spatial and Temporal Variabilities of Gross Primary Production Using MAIAC MODIS Data. Remote Sens. 2019, 11, 874. https://doi.org/10.3390/rs11070874
Hua, L.; Wang, H.; Sui, H.; Wardlow, B.; Hayes, M.J.; Wang, J. Mapping the Spatial-Temporal Dynamics of Vegetation Response Lag to Drought in a Semi-Arid Region. Remote Sens. 2019, 11, 1873. https://doi.org/10.3390/rs11161873
2017
1. Foster, T.; Brozovic, N.; Butler, A.P.; Neale, C.M.U.; Raes, D.; Steduto, P.; Fereres, E.; Hsiao, T.C. AquaCrop-OS: An open source version of FAO's crop water productivity model. Agricultural Water Management 2017, 181, 18-22.
2. Gibson, J.; Franz, T.; Wang, T.; Eisenhauer, D. A case study of field-scale maize irrigation patterns in western Nebraska: Implications to water managers and recommendations for hyper-resolution land surface modelling. Hydrology and Earth System Sciences Discussions 2017, 21, 1051–1062. https://doi.org/10.5194/hess-21-1051-2017
3. Williamson, S.N.; Hik, D.S.; Gamon, J.A.; Jarosch, A.H.; Anslow, F.S.; Clarke, G.K.C.; Rupp, T.S. SPRIng and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered Sub-Arctic mountains. Remote Sensing of Environment 2017, 189, 14-24.
4. Zambrano, F.; Wardlow, B.; Tadesse, T.; Lillo-Saavedra, M.; Lagos, O. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile. Atmospheric Research 2017, 186, 26-42.
2016
1. Ambika, A.K.; Wardlow, B.; Mishra, V. Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015. Scientific Data 2016, 3.
2. Avery, W.A.; Finkenbiner, C.; Franz, T.E.; Wang, T.J.; Nguy-Robertson, A.L.; Suyker, A.; Arkebauer, T.; Munoz-Arriola, F. Incorporation of globally available datasets into the roving cosmic-ray neutron probe method for estimating field-scale soil water content. Hydrology and Earth System Sciences 2016, 20, 3859-3872.
3. Campos, I.; Balbontin, C.; Gonzalez-Piqueras, J.; Gonzalez-Dugo, M.P.; Neale, C.M.U.; Calera, A. Combining a water balance model with evapotranspiration measurements to estimate total available soil water in irrigated and rainfed vineyards. Agricultural Water Management 2016, 165, 141-152.
4. Corcoles, J.I.; Frizzone, J.A.; Lima, S.; Mateos, L.; Neale, C.M.U.; Snyder, R.L.; Souza, F. Irrigation advisory service and performance indicators in Baixo Acarau Irrigation District, Brazil. Irrigation and Drainage 2016, 65, 61-72.
5. Emmerton, C.A.; St Louis, V.L.; Humphreys, E.R.; Gamon, J.A.; Barker, J.D.; Pastorello, G.Z. Net ecosystem exchange of CO2 with rapidly changing high arctic landscapes. Global Change Biology 2016, 22, 1185-1200.
6. Gamon, J.A.; Huemmrich, K.F.; Wong, C.Y.S.; Ensminger, I.; Garrity, S.; Hollinger, D.Y.; Noormets, A.; Penuelas, J. A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers. Proceedings of the National Academy of Sciences of the United States of America 2016, 113, 13087-13092.
7. King, E.G.; Franz, T.E. Combining ecohydrologic and transition probability-based modeling to simulate vegetation dynamics in a semi-arid rangeland. Ecological Modelling 2016, 329, 41-63.
8. Neale, C.M.U.; Jaworowski, C.; Heasler, H.; Sivarajan, S.; Masih, A. Hydrothermal monitoring in Yellowstone National Park using airborne thermal infrared remote sensing. Remote Sensing of Environment 2016, 184, 628-644.
9. Nestola, E.; Calfapietra, C.; Emmerton, C.A.; Wong, C.Y.S.; Thayer, D.R.; Gamon, J.A. Monitoring grassland seasonal carbon dynamics, by integrating MODIS NDVI, proximal optical sampling, and eddy covariance measurements. Remote Sensing 2016, 8.
10. Odi-Lara, M.; Campos, I.; Neale, C.M.U.; Ortega-Farias, S.; Poblete-Echeverria, C.; Balbontin, C.; Calera, A. Estimating evapotranspiration of an apple orchard using a remote sensing-based soil water balance. Remote Sensing 2016, 8.
11. Otkin, J.A.; Anderson, M.C.; Hain, C.; Svoboda, M.; Johnson, D.; Mueller, R.; Tadesse, T.; Wardlow, B.; Brown, J. Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought. Agricultural and Forest Meteorology 2016, 218, 230-242.
12. Schreiner-McGraw, A.P.; Vivoni, E.R.; Mascaro, G.; Franz, T.E. Closing the water balance with cosmic-ray soil moisture measurements and assessing their relation to evapotranspiration in two semiarid watersheds. Hydrology and Earth System Sciences 2016, 20, 329-345.
13. Semeradova, D.; Trnka, M.; Hlavinka, P.; Balek, J.; Bohovic, R.; Tadesse, T.; Hayes, M.; Wardlow, B.; Zalud, Z. Detection of drought events using combination of satellite data and soil moisture modelling. Mendel and Bioclimatology 2016, 299-305.
14. Wang, R.; Gamon, J.A.; Emmerton, C.A.; Li, H.T.; Nestola, E.; Pastorello, G.Z.; Menzer, O. Integrated analysis of productivity and biodiversity in a southern Alberta prairie. Remote Sensing 2016, 8.
15. Wang, R.; Gamon, J.A.; Montgomery, R.A.; Townsend, P.A.; Zygielbaum, A.I.; Bitan, K.; Tilman, D.; Cavender-Bares, J. Seasonal variation in the NDVI-species richness relationship in a prairie grassland experiment (Cedar Creek). Remote Sensing 2016, 8.
16. Wang, T.J.; Franz, T.E.; Yue, W.F.; Szilagyi, J.; Zlotnik, V.A.; You, J.S.; Chen, X.H.; Shulski, M.D.; Young, A. Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network. Journal of Hydrology 2016, 533, 250-265.
17. Wehlage, D.C.; Gamon, J.A.; Thayer, D.; Hildebrand, D.V. Interannual variability in dry mixed-grass prairie yield: A comparison of MODIS, SPOT, and field measurements. Remote Sensing 2016, 8.
18. Williamson, S.N.; Barrio, I.C.; Hik, D.S.; Gamon, J.A. Phenology and species determine growing-season albedo increase at the altitudinal limit of shrub growth in the Sub-Arctic. Global Change Biology 2016, 22, 3621-3631.
19. Xia, T.; Kustas, W.P.; Anderson, M.C.; Alfieri, J.G.; Gao, F.; McKee, L.; Prueger, J.H.; Geli, H.M.E.; Neale, C.M.U.; Sanchez, L., et al. Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes. Hydrology and Earth System Sciences 2016, 20, 1523-1545.
20. Yue, W.F.; Wang, T.J.; Franz, T.E.; Chen, X.H. Spatiotemporal patterns of water table fluctuations and evapotranspiration induced by riparian vegetation in a semiarid area. Water Resources Research 2016, 52, 1948-1960.
21. Zeng, L.L.; Wardlow, B.D.; Wang, R.; Shan, J.; Tadesse, T.; Hayes, M.J.; Li, D.R. A hybrid approach for detecting corn and soybean phenology with time-series MODIS data. Remote Sensing of Environment 2016, 181, 237-250.
2015
1. AghaKouchak, A.; Farahmand, A.; Melton, F.S.; Teixeira, J.; Anderson, M.C.; Wardlow, B.D.; Hain, C.R. Remote sensing of drought: Progress, challenges and opportunities. Reviews of Geophysics 2015, 53, 452-480.
2. Biudes, M.S.; Vourlitis, G.L.; Machado, N.G.; de Arruda, P.H.Z.; Neves, G.A.R.; Lobo, F.D.; Neale, C.M.U.; Nogueira, J.D. Patterns of energy exchange for tropical ecosystems across a climate gradient in Mato Grosso, Brazil. Agricultural and Forest Meteorology 2015, 202, 112-124.
3. Bohovic, R.; Hlavinka, P.; Semeradova, D.; Balek, J.; Tadesse, T.; Hayes, M.; Wardlow, B.; Trnka, M. LINCOLN - an algorithm for filtering daily NDVI MODIS data and deriving the start of the season. In Global Change: a Complex Challenge. 2015; p 42-45.
4. Flanagan, L.B.; Sharp, E.J.; Gamon, J.A. Application of the photosynthetic light-use efficiency model in a northern Great Plains grassland. Remote Sensing of Environment 2015, 168, 239-251.
5. Franz, T.E.; Wang, T.J.; Avery, W.; Finkenbiner, C.; Brocca, L. Combined analysis of soil moisture measurements from roving and fixed cosmic ray neutron probes for multiscale real-time monitoring. Geophysical Research Letters 2015, 42, 3389-3396.
6. Gamon, J.A. Reviews and syntheses: Optical sampling of the flux tower footPRInt. Biogeosciences 2015, 12, 4509-4523.
7. Gamon, J.A.; Kovalchuck, O.; Wong, C.Y.S.; Harris, A.; Garrity, S.R. Monitoring seasonal and diurnal changes in photosynthetic pigments with automated PRI and NDVI sensors. Biogeosciences 2015, 12, 4149-4159.
8. Gamon, J.A.; Wang, R.; Stilwell, A.; Zygielbaum, A.I.; Cavender-Bares, J.; Townsend, P.A. In The scale dependence of optical diversity in a prairie ecosystem, Ecological Society of America, Fort Lauderdale, Florida, USA, 2015; Fort Lauderdale, Florida, USA.
9. Gitelson, A.A.; Gamon, J.A. The need for a common basis for defining light-use efficiency: Implications for productivity estimation. Remote Sensing of Environment 2015, 156, 196-201.
10. Glenn, D.T.; Endter-Wada, J.; Kjelgren, R.; Neale, C.M.U. Tools for evaluating and monitoring effectiveness of urban landscape water conservation interventions and programs. Landscape and Urban Planning 2015, 139, 82-93.
11. Otkin, J.A.; Shafer, M.; Svoboda, M.; Wardlow, B.; Anderson, M.C.; Hain, C.; Basara, J. Facilitating the use of drought early warning information through interactions with agricultural stakeholders. Bulletin of the American Meteorological Society 2015, 96, 1073-1078.
12. Tadesse, T.; Wardlow, B.D.; Brown, J.F.; Svoboda, M.D.; Hayes, M.J.; Fuchs, B.; Gutzmer, D. Assessing the vegetation condition impacts of the 2011 drought across the US southern Great Plains using the Vegetation Drought Response Index (VegDRI). Journal of Applied Meteorology and Climatology 2015, 54, 153-169.
13. Taghvaeian, S.; Neale, C.M.U.; Osterberg, J.; Sritharan, S.I.; Watts, D.R. Water use and stream-aquifer-phreatophyte interaction along a tamarisk-dominated segment of the lower Colorado River. In Remote sensing of the terrestrial water cycle, Lakshmi, V.; Alsdorf, D.; Anderson, M.; Biancamaria, S.; Cosh, M.; Entin, J.; Huffman, G.; Kustas, W.; VanOevelen, P.; Painter, T., et al., Eds. 2015; Vol. 206, pp 95-113.
14. Trnka, M.; Brazdil, R.; Mozny, M.; Stepanek, P.; Dobrovolny, P.; Zahradnicek, P.; Balek, J.; Semeradova, D.; Dubrovsky, M.; Hlavinka, P., et al. Soil moisture trends in the Czech Republic between 1961 and 2012. International Journal of Climatology 2015, 35, 3733-3747.
15. Wang, T.J.; Franz, T.E. Field observations of regional controls of soil hydraulic properties on soil moisture spatial variability in different climate zones. Vadose Zone Journal 2015, 14.
16. Wang, T.J.; Franz, T.E.; Zlotnik, V.A. Controls of soil hydraulic characteristics on modeling groundwater recharge under different climatic conditions. Journal of Hydrology 2015, 521, 470-481.
17. Wang, T.J.; Franz, T.E.; Zlotnik, V.A.; You, J.S.; Shulski, M.D. Investigating soil controls on soil moisture spatial variability: Numerical simulations and field observations. Journal of Hydrology 2015, 524, 576-586.
18. Wang, T.J.; Wedin, D.A.; Franz, T.E.; Hiller, J. Effect of vegetation on the temporal stability of soil moisture in grass-stabilized semi-arid sand dunes. Journal of Hydrology 2015, 521, 447-459.
19. Wong, C.Y.S.; Gamon, J.A. The Photochemical Reflectance Index provides an optical indicator of sPRIng photosynthetic activation in evergreen conifers. New Phytologist 2015, 206, 196-208.
20. Wong, C.Y.S.; Gamon, J.A. Three causes of variation in the Photochemical Reflectance Index (PRI) in evergreen conifers. New Phytologist 2015, 206, 187-195.
21. Woodbury, B.; Eigenberg, R.; Franz, T.E. Resistivity arrays as an early warning system for monitoring runoff holding ponds. Journal of Environmental and Engineering Geophysics 2015, 20, 319-335.
22. Zeng, L.L.; Wardlow, B.D.; Tadesse, T.; Shan, J.; Hayes, M.J.; Li, D.R.; Xiang, D.X. Estimation of daily air temperature based on MODIS land surface temperature products over the corn belt in the US. Remote Sensing 2015, 7, 951-970.
2014
1. Almeida, A.C.; Dutta, R.; Franz, T.E.; Terhorst, A.; Smethurst, P.J.; Baillie, C.; Worledge, D. Combining cosmic-ray neutron and capacitance sensors and fuzzy inference to spatially quantify soil moisture distribution. IEEE Sensors Journal 2014, 14, 3465-3472.
2. Campos, I.; Neale, C.M.U.; Lopez, M.L.; Balbontin, C.; Calera, A. Analyzing the effect of shadow on the relationship between ground cover and vegetation indices by using spectral mixture and radiative transfer models. Journal of Applied Remote Sensing 2014, 8.
3. Gilmanov, T.G.; Baker, J.M.; Bernacchi, C.J.; Billesbach, D.P.; Burba, G.G.; Castro, S.; Chen, J.; Eugster, W.; Fischer, M.L.; Gamon, J.A., et al. Productivity and carbon dioxide exchange of leguminous crops: Estimates from flux tower measurements. Agronomy Journal 2014, 106, 545-559.
4. Harris, A.; Gamon, J.A.; Pastorello, G.Z.; Wong, C.Y.S. Retrieval of the Photochemical Reflectance Index for assessing xanthophyll cycle activity: A comparison of near-surface optical sensors. Biogeosciences 2014, 11, 6277-6292.
5. Hunt, E.D.; Svoboda, M.; Wardlow, B.; Hubbard, K.; Hayes, M.; Arkebauer, T. Monitoring the effects of rapid onset of drought on non-irrigated maize with agronomic data and climate-based drought indices. Agricultural and Forest Meteorology 2014, 191, 1-11.
6. Lewis, C.S.; Geli, H.M.E.; Neale, C.M.U. Comparison of the NLDAS weather forcing model to agrometeorological measurements in the western United States. Journal of Hydrology 2014, 510, 385-392.
7. Lv, L.; Franz, T.E.; Robinson, D.A.; Jones, S.B. Measured and modeled soil moisture compared with cosmic-ray neutron probe estimates in a mixed forest. Vadose Zone Journal 2014, 13.
8. McJannet, D.; Franz, T.E.; Hawdon, A.; Boadle, D.; Baker, B.; Almeida, A.; Silberstein, R.; Lambert, T.; Desilets, D. Field testing of the universal calibration function for determination of soil moisture with cosmic-ray neutrons. Water Resources Research 2014, 50, 5235-5248.
9. Paul, G.; Gowda, P.H.; Prasad, P.V.V.; Howell, T.A.; Aiken, R.M.; Neale, C.M.U. Investigating the influence of roughness length for heat transport (z(oh)) on the performance of SEBAL in semi-arid irrigated and dryland agricultural systems. Journal of Hydrology 2014, 509, 231-244.
10. Rosolem, R.; Hoar, T.; Arellano, A.; Anderson, J.L.; Shuttleworth, W.J.; Zeng, X.; Franz, T.E. Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale. Hydrology and Earth System Sciences 2014, 18, 4363-4379.
11. Stillman, S.; Ninneman, J.; Zeng, X.B.; Franz, T.E.; Scott, R.L.; Shuttleworth, W.J.; Cummins, K. Summer soil moisture spatiotemporal variability in southeastern Arizona. Journal of Hydrometeorology 2014, 15, 1473-1485.
12. van Opstal, J.D.; Neale, C.M.U.; Lecina, S. Improvements in irrigation system modelling when using remotely-sensed et for calibration. In Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, Neale, C.M.U.; Maltese, A., Eds. 2014; Vol. 9239.
13. Vanderlinder, M.S.; Neale, C.M.U.; Rosenberg, D.E.; Kettenring, K.M. Use of remote sensing to assess changes in wetland plant communities over an 18-year period: A case study from the Bear River Migratory Bird Refuge, Great Salt Lake, Utah. Western North American Naturalist 2014, 74, 33-46.
14. Wardlow, B.D.; Callahan, K. A multi-scale accuracy assessment of the MODIS irrigated agriculture data-set (MIRAD) for the state of Nebraska, USA. GIScience & Remote Sensing 2014, 51, 575-592.
15. Williamson, S.N.; Hik, D.S.; Gamon, J.A.; Kavanaugh, J.L.; Flowers, G.E. Estimating temperature fields from MODIS land surface temperature and air temperature observations in a Sub-Arctic alpine environment. Remote Sensing 2014, 6, 946-963.
16. Zaccaria, D.; Neale, C.M.U. Modeling delivery performance in pressurized irrigation systems from simulated peak-demand flow configurations. Irrigation Science 2014, 32, 295-317.
2013
1. Anderson, M.C.; Hain, C.; Otkin, J.; Zhan, X.W.; Mo, K.; Svoboda, M.; Wardlow, B.; Pimstein, A. An intercomparison of drought indicators based on thermal remote sensing and NLDAS-2 simulations with US drought monitor classifications. Journal of Hydrometeorology 2013, 14, 1035-1056.
2. Franz, T.E.; Zreda, M.; Ferre, T.P.A.; Rosolem, R. An assessment of the effect of horizontal soil moisture heterogeneity on the area-average measurement of cosmic-ray neutrons. Water Resources Research 2013, 49, 6450-6458.
3. Franz, T.E.; Zreda, M.; Rosolem, R.; Ferre, T.P.A. A universal calibration function for determination of soil moisture with cosmic-ray neutrons. Hydrology and Earth System Sciences 2013, 17, 453-460.
4. Franz, T.E.; Zreda, M.; Rosolem, R.; Hornbuckle, B.K.; Irvin, S.L.; Adams, H.; Kolb, T.E.; Zweck, C.; Shuttleworth, W.J. Ecosystem-scale measurements of biomass water using cosmic ray neutrons. Geophysical Research Letters 2013, 40, 3929-3933.
5. Gamon, J.A.; Huemmrich, K.F.; Stone, R.S.; Tweedie, C.E. Spatial and temporal variation in PRImary productivity (NDVI) of coastal Alaskan tundra: Decreased vegetation growth following earlier snowmelt. In Remote sensing of environment, 2013; Vol. 129, pp 144-153.
6. Huemmrich, K.F.; Gamon, J.A.; Tweedie, C.E.; Campbell, P.K.E.; Landis, D.R.; Middleton, E.M. Arctic tundra vegetation functional types based on photosynthetic physiology and optical properties. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2013, 6, 265-275.
7. Jaworowski, C.; Heasler, H.; Neale, C.; Saravanan, S.; Masih, A. Temporal and seasonal variations of the hot sPRIng basin hydrothermal system, Yellowstone National Park, USA. Remote Sensing 2013, 5, 6587-6610.
8. Neale, C.M.U.; Maltese, A. Introduction. In Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, Neale, C.M.U.; Maltese, A., Eds. 2013; Vol. 8887, pp XIII-XIII.
9. Nguy-Robertson, A.; Gitelson, A.; Peng, Y.; Walter-Shea, E.; Leavitt, B.; Arkebauer, T. Continuous monitoring of crop reflectance, vegetation fraction, and identification of developmental stages using a four band radiometer. Agronomy Journal 2013, 105, 1769-1779.
10. Paul, G.; Gowda, P.H.; Prasad, P.V.V.; Howell, T.A.; Staggenborg, S.A.; Neale, C.M.U. Lysimetric evaluation of SEBAL using high resolution airborne imagery from BEAREX08. Advances in Water Resources 2013, 59, 157-168.
11. Rasaiah, B.A.; Malthus, T.J.; Bellman, C.; Chisholm, L.; Gamon, J.; Hueni, A.; Huete, A.; Jones, S.D.; Ong, C.; Phinn, S., et al. Approaches to establishing a metadata standard for field spectroscopy datasets. 2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2013, 4523-4525.
12. Rosolem, R.; Shuttleworth, W.J.; Zreda, M.; Franz, T.E.; Zeng, X.; Kurc, S.A. The effect of atmospheric water vapor on neutron count in the cosmic-ray soil moisture observing system. Journal of Hydrometeorology 2013, 14, 1659-1671.
13. Shuttleworth, J.; Rosolem, R.; Zreda, M.; Franz, T.E. The cosmic-ray soil moisture interaction code (cosmic) for use in data assimilation. Hydrology and Earth System Sciences 2013, 17, 3205-3217.
14. Stilwell, A.R.; Hein, G.L.; Zygielbaum, A.I.; Rundquist, D.C. Proximal sensing to detect symptoms associated with wheat curl mite-vectored viruses. International Journal of Remote Sensing 2013, 34, 4951-4966.
15. Swain, S.; Wardlow, B.D.; Narumalani, S.; Rundquist, D.C.; Hayes, M.J. Relationships between vegetation indices and root zone soil moisture under maize and soybean canopies in the US corn belt: A comparative study using a close-range sensing approach. International Journal of Remote Sensing 2013, 34, 2814-2828.
16. Teixeira, A.H.D.; Lopes, H.L.; Hernandez, F.B.T.; Sherer-Warren, M.; Andrade, R.G.; Neale, C.M.U. Retrieving water productivity parameters by using LandSAT images in the Nilo Coelho Irrigation Scheme, Brazil. In Remote sensing for agriculture, ecosystems, and hydrology xv, Neale, C.M.U.; Maltese, A., Eds. 2013; Vol. 8887.
17. Teixeira, A.H.D.; Scherer-Warren, M.; Lopes, H.L.; Hernandez, F.B.T.; Andrade, R.G.; Neale, C.M.U. Application of MODIS images for modelling the energy balance components in the semi-arid conditions of Brazil. In Remote sensing for agriculture, ecosystems, and hydrology xv, Neale, C.M.U.; Maltese, A., Eds. 2013; Vol. 8887.
18. Townsend, P.A.; Serbin, S.P.; Kruger, E.L.; Gamon, J.A. Disentangling the contribution of biological and physical properties of leaves and canopies in imaging spectroscopy data. Proceedings of the National Academy of Sciences of the United States of America 2013, 110, E1074-E1074.
19. Trnka, M.; Kersebaum, K.C.; Eitzinger, J.; Hayes, M.; Hlavinka, P.; Svoboda, M.; Dubrovsky, M.; Semeradova, D.; Wardlow, B.; Pokorny, E., et al. Consequences of climate change for the soil climate in central Europe and the central plains of the United States. Climatic Change 2013, 120, 405-418.
20. Williamson, S.N.; Hik, D.S.; Gamon, J.A.; Kavanaugh, J.L.; Koh, S. Evaluating cloud contamination in clear-sky MODIS terra daytime land surface temperatures using ground-based meteorology station observations. Journal of Climate 2013, 26, 1551-1560.
21. Zaccaria, D.; Lamaddalena, N.; Neale, C.M.U.; Merkley, G.P. Simulation of peak-demand hydrographs in pressurized irrigation delivery systems using a deterministic-stochastic combined model. Part II: Model applications. Irrigation Science 2013, 31, 193-208.
22. Zaccaria, D.; Lamaddalena, N.; Neale, C.M.U.; Merkley, G.P.; Palmisano, N.; Passarella, G. Simulation of peak-demand hydrographs in pressurized irrigation delivery systems using a deterministic-stochastic combined model. Part I: Model development. Irrigation Science 2013, 31, 209-224.
2012
1. Abdalla, S.H.; Neale, C.M.U. Modelling sensible heat flux for sparse arid natural ecosystems using multispectral video imagery. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 158-161.
2. Alfieri, J.G.; Kustas, W.P.; Prueger, J.H.; Chavez, J.L.; Evett, S.R.; Neale, C.M.U.; Anderson, M.C.; Hipps, L.E.; Copeland, K.S.; Howell, T.A., et al. A comparison of the eddy covariance and lysimetry-based measurements of the surface energy fluxes during BEAREX08. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 215-218.
3. Alfieri, J.G.; Kustas, W.P.; Prueger, J.H.; Hipps, L.E.; Evett, S.R.; Basara, J.B.; Neale, C.M.U.; French, A.N.; Colaizzi, P.; Agam, N., et al. On the discrepancy between eddy covariance and lysimetry-based surface flux measurements under strongly advective conditions. Advances in Water Resources 2012, 50, 62-78.
4. Alvarez-Anorve, M.Y.; Quesada, M.; Sanchez-Azofeifa, G.A.; Avila-Cabadilla, L.D.; Gamon, J.A. Functional regeneration and spectral reflectance of trees during succession in a highly diverse tropical dry forest ecosystem. American Journal of Botany 2012, 99, 816-826.
5. Bingham, Q.G.; Neilson, B.T.; Neale, C.M.U.; Cardenas, M.B. Application of high-resolution, remotely sensed data for transient storage modeling parameter estimation. Water Resources Research 2012, 48.
6. Calera, A.; Osann, A.; D'Urso, G.; Neale, C.; Moreno, J.M.; Partners, P.L. Earth observation for irrigation and river basin management in an operational way: The spider system. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 423-426.
7. Campos, I.; Calera, A.; Balbontin, C.; Torres, E.A.; Gonzalez-Piqueras, J.; Neale, C.M.U. Basal crop coefficient from remote sensing assessment in rain-fed grapes in southeast Spain. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 397-400.
8. Chavez, J.L.; Gowda, P.H.; Howell, T.A.; Garcia, L.A.; Copeland, K.S.; Neale, C.M.U. ET mapping with high-resolution airborne remote sensing data in an advective semiarid environment. Journal of Irrigation and Drainage Engineering-ASCE 2012, 138, 416-423.
9. Franz, T.E.; Caylor, K.K.; King, E.G.; Nordbotten, J.M.; Celia, M.A.; Rodriguez-Iturbe, I. An ecohydrological approach to predicting hillslope-scale vegetation patterns in dryland ecosystems. Water Resources Research 2012, 48.
10. Franz, T.E.; Zreda, M.; Ferre, T.P.A.; Rosolem, R.; Zweck, C.; Stillman, S.; Zeng, X.; Shuttleworth, W.J. Measurement depth of the cosmic ray soil moisture probe affected by hydrogen from various sources. Water Resources Research 2012, 48.
11. Franz, T.E.; Zreda, M.; Rosolem, R.; Ferre, T.P.A. Field validation of a cosmic-ray neutron sensor using a distributed sensor network. Vadose Zone Journal 2012, 11.
12. Gamon, J.A.; Berry, J.A. Facultative and constitutive pigment effects on the Photochemical Reflectance Index (PRI) in sun and shade conifer needles. Israel Journal of Plant Sciences 2012, 60, 85-95.
13. Gamon, J.A.; Kershaw, G.P.; Williamson, S.; Hik, D.S. Microtopographic patterns in an arctic baydjarakh field: Do fine-grain patterns enforce landscape stability? Environmental Research Letters 2012, 7.
14. Geli, H.M.E.; Neale, C.M.U. Spatial evapotranspiration modelling interface (SETMI). In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 171-174.
15. Geli, H.M.E.; Neale, C.M.U.; Watts, D.R.; Osterberg, J.; Pack, R.T. Incorporating LiDAR data into scintillometer-based estimates of sensible heat flux considering different atmospheric stability conditions. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 191-194.
16. Hornbuckle, B.; Irvin, S.; Franz, T.E.; Rosolem, R.; Zweck, C.; IEEE. The potential of the cosmos network to be a source of new soil moisture information for SMOS and SMAP. In 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012; pp 1243-1246.
17. Jaworowski, C.; Heasler, H.P.; Neale, C.M.U.; Sivarajan, S.; Masih, A. Monitoring the dynamic geohydrology of the Upper Geyser Basin, Yellowstone National Park: An integration of airborne thermal infrared and LiDAR imagery. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 54-58.
18. Kandiah, R.; Wei, X.F.; Sritharan, S.; Watts, D.; Neale, C.; Osterberg, J.; Chatterjee, S. Ground-based riparian evapotranspiration measurements for remote sensing algorithms. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 206-209.
19. King, E.G.; Franz, T.E.; Caylor, K.K. Ecohydrological interactions in a degraded two-phase mosaic dryland: Implications for regime shifts, resilience, and restoration. Ecohydrology 2012, 5, 733-745.
20. Kustas, W.P.; Alfieri, J.G.; Anderson, M.C.; Colaizzi, P.D.; Prueger, J.H.; Chavez, J.L.; Neale, C.M.U.; Dulaney, W.; Evett, S.R.; Copeland, K.S., et al. Utility of the thermal-based dual-temperature-difference technique under strongly advective conditions during BEAREX08. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 145-148.
21. Kustas, W.P.; Alfieri, J.G.; Anderson, M.C.; Colaizzi, P.D.; Prueger, J.H.; Evett, S.R.; Neale, C.M.U.; French, A.N.; Hipps, L.E.; Chavez, J.L., et al. Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area. Advances in Water Resources 2012, 50, 120-133.
22. Malhotra, B.; Gamon, J.A.; Bressan, S. Salsa: A software system for data management and analytics in field spectrometry. In Scientific and statistical database management, SSDBM 2012, Ailamaki, A.; Bowers, S., Eds. 2012; Vol. 7338, pp 634-639.
23. Meyer, G.E.; Paparozzi, E.T.; Walter-Shea, E.A.; Blankenship, E.E.; Adams, S.A. An investigation of reflective mulches for use over capillary mat systems for winter-time greenhouse strawberry production. Applied Engineering in Agriculture 2012, 28, 271-279.
24. Miller, G.R.; Cable, J.M.; McDonald, A.K.; Bond, B.; Franz, T.E.; Wang, L.X.; Gou, S.; Tyler, A.P.; Zou, C.B.; Scott, R.L. Understanding ecohydrological connectivity in savannas: A system dynamics modelling approach. Ecohydrology 2012, 5, 200-220.
25. Neale, C.M.U.; Geli, H.M.E.; Kustas, W.P.; Alfieri, J.G.; Gowda, P.H.; Evett, S.R.; Prueger, J.H.; Hipps, L.E.; Dulaney, W.P.; Chavez, J.L., et al. Soil water content estimation using a remote sensing based hybrid evapotranspiration modeling approach. Advances in Water Resources 2012, 50, 152-161.
26. Neale, C.M.U.; Maltese, A. Remote sensing for agriculture, ecosystems, and hydrology XIV Introduction. In Remote sensing for agriculture, ecosystems, and hydrology xiv, Neale, C.M.U.; Maltese, A., Eds. 2012; Vol. 8531.
27. Neale, C.M.U.; Sivarajan, S.; Masih, A.; Jaworowski, C.; Heasler, H. Thermal remote sensing of snow cover to identify the extent of hydrothermal areas in Yellowstone National Park. In Remote sensing for agriculture, ecosystems, and hydrology xiv, Neale, C.M.U.; Maltese, A., Eds. 2012; Vol. 8531.
28. Prueger, J.H.; Alfieri, J.G.; Hipps, L.E.; Kustas, W.P.; Chavez, J.L.; Evett, S.R.; Anderson, M.C.; French, A.N.; Neale, C.M.U.; McKee, L.G., et al. Patch scale turbulence over dryland and irrigated surfaces in a semi-arid landscape under advective conditions during BEAREX08. Advances in Water Resources 2012, 50, 106-119.
29. Prueger, J.H.; Alfieri, J.; Kustas, W.; Hipps, L.; Neale, C.; Evett, S.R.; Hatfield, J.; McKee, L.G.; Chavez, J.L. Thermal radiation and energy closure assessment in evapotranspiration estimation for remote sensing validation. 2012; p 87-109.
30. Sakamoto, T.; Gitelson, A.A.; Nguy-Robertson, A.L.; Arkebauer, T.J.; Wardlow, B.D.; Suyker, A.E.; Verma, S.B.; Shibayama, M. An alternative method using digital cameras for continuous monitoring of crop status. Agricultural and Forest Meteorology 2012, 154, 113-126.
31. Sakamoto, T.; Gitelson, A.A.; Wardlow, B.D.; Arkebauer, T.J.; Verma, S.B.; Suyker, A.E.; Shibayama, M. Application of day and night digital photographs for estimating maize biophysical characteristics. Precision Agriculture 2012, 13, 285-301.
32. Sritharan, S.I.; Khanal, P.; Wei, X.F.; Kandiah, R.; Hatfield, M.H.; Neale, C.; Osterberg, J. Stream-aquifer interaction assessment using riparian evapotranspiration estimates from remote sensing algorithms. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 231-234.
33. Swain, S.; Rundquist, D.; Arkebauer, T.J.; Narumalani, S.; Wardlow, B. Non-invasive estimation of relative water content in soybean leaves using infrared thermography. Israel Journal of Plant Sciences 2012, 60, 25-36.
34. Taghvaeian, S.; Neale, C.M.U.; Dos Santos, C.A.C.; Watts, D.; Osterberg, J.; Sritharan, S.I. Two different remote sensing techniques for monitoring crop coefficient and water requirement of cotton. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 89-93.
35. Terletzky, P.; Ramsey, R.D.; Neale, C.M.U. Spectral characteristics of domestic and wild mammals. GIScience & Remote Sensing 2012, 49, 597-608.
36. Wang, L.X.; Zou, C.; O'Donnell, F.; Good, S.; Franz, T.E.; Miller, G.R.; Caylor, K.K.; Cable, J.M.; Bond, B. Characterizing ecohydrological and biogeochemical connectivity across multiple scales: A new conceptual framework. Ecohydrology 2012, 5, 221-233.
37. Wei, X.F.; Sritharan, S.I.; Kandiah, R.; Osterberg, J.; Neale, C.; Farrow, K.; Davenport, J. Implementation of SEBAL algorithm with LandSAT Thematic Mapper 5 in lower Colorado River Basin. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 98-101.
38. Welsh, A.P.; Neale, C.M.U.; Endter-Wada, J.; Kjelgren, R.K. Custom software application for analysing urban landscape water use. In Remote sensing and hydrology, Neale, C.M.U.; Cosh, M.H., Eds. 2012; Vol. 352, pp 162-166.
39. Zaman, B.; McKee, M.; Neale, C.M.U. Fusion of remotely sensed data for soil moisture estimation using relevance vector and support vector machines. International Journal of Remote Sensing 2012, 33, 6516-6552.
40. Zreda, M.; Shuttleworth, W.J.; Zeng, X.; Zweck, C.; Desilets, D.; Franz, T.E.; Rosolem, R. Cosmos: The cosmic-ray soil moisture observing system. Hydrology and Earth System Sciences 2012, 16, 4079-4099.
41. Zygielbaum, A.I.; Arkebauer, T.J.; Walter-Shea, E.A.; Scoby, D.L. Detection and measurement of vegetation photoprotection stress response using par reflectance. Israel Journal of Plant Sciences 2012, 60, 37-47.
Older publications:
Gitelson, A., J. Schalles, D. Rundquist, F. Schiebe, and Y. Yacobi, 1999. Comparative reflectance properties of algal cultures with manipulated densities. Journal of Applied Phycology.
Schalles, J., D. Rundquist, and F. Schiebe, 1999. The influence of suspended clays on phytoplankton reflectance signatures and the remote estimation of chlorophyll. Proceedings, International Association of Theoretical and Applied Limnology.
Lodhi, M., D. Rundquist, L. Han, and M. Kuzila, 1998. Estimation of suspended sediment concentration in water using integrated surface reflectance. GeoCarto International, 13:2, 11-15.
Han, L. and D. Rundquist, 1998. The impact of a wind-roughened water surface on remote measurements of turbidity. International Journal of Remote Sensing, 19:1, 195-201.
Lodhi, M., D. Rundquist, L. Han, and M. Kuzila, 1997. The potential for detecting loess soils suspended in surface water using remote sensing. Water Resources Bulletin, 33:1, 111-117.
Rundquist, D., B. Leavitt, S. Payton, and R. Narayanan, 1997. Using ERS-1 data to measure and map selected conditions related to the production of methane in a wetland environment: the Nebraska Sandhills, USA. Proceedings, Third ERS Symposium, 197-202.
Han, L. and D. Rundquist, 1997. Comparison of NIR/RED ratio and first derivative of reflectance in estimating algal-chlorophyll concentration: a case study in a turbid reservoir. Remote Sensing of Environment, 62:253-261.
Goodin, D., J. Harrington, Jr., M. Nellis, and D. Rundquist, 1996. Mapping reservoir turbidity patterns using SPOT-HRV data. GeoCarto International, 11:4, 71-78.
Han, L. and D. Rundquist, 1996. Spectral characterization of suspended sediments generated from two texture classes of clay soil. International Journal of Remote Sensing, 17:3, 643-649.
Rundquist, D., L. Han, J. Schalles, and J. Peake, 1996. Remote measurement of algal chlorophyll in surface waters: the case for the first derivative of reflectance near 690 nm. Photogrammetric Engineering and Remote Sensing, 62:2, 195-200.
Rundquist, D., J. Schalles, and J. Peake, 1995. The response of volume reflectance to manipulated chlorophyll concentrations above bright and dark bottoms at various depths in experimental tanks. GeoCarto International, 10:4, 5-14.
Han, L., D. Rundquist, L. Liu, R. Fraser, and J. Schalles, 1994. The spectral responses of algal chlorophyll in water with varying levels of suspended sediment. International Journal of Remote Sensing, 15:18, 3707-3718.
Han, L. and D. Rundquist, 1994. The response of both surface reflectance and the underwater light field to various levels of suspended sediments: preliminary results. Photogrammetric Engineering and Remote Sensing, 60:12, 1463-1471.
Narayanan, R., R. Pardipuram, and D. Rundquist, 1994. Statistical characteristics of simulated radar imagery from bare soil surfaces. IEEE Transactions on Geoscience and Remote Sensing, 32:1, 159-168.
Narayanan, R., D. Doerr, and D. Rundquist, 1994. Power spectrum of wind-influenced vegetation backscatter at x-band. IEEE Proceedings on Radar and Sonar Navigation, 141:2, 125-131.
Price, K., V. Varner, E. Martinko, D. Rundquist, and J. Peake. Influences of land management and weather on plant biophysical and hyperspectral response patterns of tallgrass prairies in Northeastern Kansas. Proceedings, PECORA-12 Symposium, 441-450.
Narayanan, R., D. Doerr, and D. Rundquist, 1992. Temporal decorrelation characteristics of x-band microwave backscatter from wind-influenced vegetation. IEEE Transactions on Aerospace and Electronics Systems, 28:2, 404-412.
