2,273
Views
7
CrossRef citations to date
0
Altmetric
Original Research Article

Drying conditions in Switzerland – indication from a 35-year Landsat time-series analysis of vegetation water content estimates to support SDGs

, , , , ORCID Icon, ORCID Icon, , & ORCID Icon show all
Pages 445-475 | Received 01 Apr 2021, Accepted 25 Aug 2021, Published online: 01 Oct 2021

References

  • Allgaier Leuch, B., Streit, K., & Brang, P. (2017). La Forêt Suisse Face Aux Changements Climatiques: Quelles Évolutions Attendre? https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A13288/.
  • Andries, A., Morse, S., Murphy, R. J., Lynch, J., & Woolliams, E. R. (2019). Seeing sustainability from space: using earth observation data to populate the un sustainable development goal indicators. Sustainability, 11(18), 5062.
  • Bajgain, R., Xiao, X., Basara, J., Wagle, P., Zhou, Y., Zhang, Y., & Mahan, H. (2017). Assessing Agricultural Drought in Summer over Oklahoma Mesonet Sites Using the Water-Related Vegetation Index from MODIS. International Journal of Biometeorology, 61(2), 377–390.
  • Beniston, M., Rebetez, M., Giorgi, F., & Marinucci, M. R. (1994). An analysis of regional climate change in Switzerland. Theoretical and Applied Climatolog,y, 49(3), 135–159.
  • Brun, P., Psomas, A., Ginzler, C., Thuiller, W., Zappa, M., & Zimmermann, N. E. (2020). Large-Scale Early-Wilting Response of Central European Forests to the 2018 Extreme Drought. Global Change Biology, 26(12), 7021–7035.
  • Brunner, M., Liechti, K., & Zappa, M. (2019). Extremeness of recent drought events in Switzerland: Dependence on variable and return period choice. Natural Hazards and Earth System Sciences, 19, 2311–2323.
  • Buras, A., Rammig, A., & Zang, C. S. (2020). Quantifying Impacts of the 2018 Drought on European Ecosystems in Comparison to 2003. Biogeosciences, 17(6), 1655–1672.
  • Bushra, N., Rohli, R. V., Lam, N. S. N., Zou, L., Bin Mostafiz, R., & Mihunov, V. (2019). The Relationship between the Normalized Difference Vegetation Index and Drought Indices in the South Central United States. Natural Hazards, 96(2), 791–808.
  • Ceccato, P., Flasse, S., & Grégoire, J. M. (2002). Designing a Spectral Index to Estimate Vegetation Water Content from Remote Sensing Data: Part 2. Validation and Applications. Remote Sensing of Environment, 82(2), 198–207.
  • Ceccato, P., Flasse, S., Tarantola, S., Jacquemoud, S., & Grégoire, J. M. (2001). Detecting Vegetation Leaf Water Content Using Reflectance in the Optical Domain. Remote Sensing of Environment, 77(1), 22–33.
  • CH2014-Impacts. (2014). Toward Quantitative Scenarios of Climate Change Impacts in Switzerland. Switzerland: Bern.
  • CH2018 (2018). CH2018 – Climate Scenarios for Switzerland, Technical Report. Zurich, Switzerland.
  • Chang, S., Wu, B., Yan, N., Davdai, B., & Nasanbat, E. (2017). Suitability Assessment of Satellite-Derived Drought Indices for Mongolian Grassland. Remote Sensing, 9(7), 650.
  • Chatenoux, B., .Richard J. -P. Small D., Roeoesli C., Wingate V., Poussin C., Rodila D., Peduzzi P., Steinmeier C., Ginzler C., Psomas A., Schaepman M., Giuliani G (in press). The Swiss Data Cube: Analysis Ready Data Archive Using Earth Observations of Switzerland, Scientific Data.
  • Cherlet, M., Hutchinson, C., Reynolds, J., Hill, J., Sommer, S., & von Maltitz, G. (Eds.). (2018). World Atlas of Desertification. Luxembourg: Publication Office of the European Union.
  • Cowie, A. L., Orr, B. J., Castillo Sanchez, V. M., Chasek, P., Crossman, N. D., Erlewein, A., Louwagie, G., Maron, M., Metternicht, G. I., Minelli, S., Tengberg, A. E., Walter, S., & Welton, S (2018). Land in Balance: The Scientific Conceptual Framework for Land Degradation Neutrality. Environmental Science & Policy, 79(January), 25–35.
  • Crocetti, L., Forkel, M., Fischer, M., Jurečka, F., Grlj, A., Salentinig, A., Trnka, M., Anderson, M., Ng, W. -T., Kokalj, Z., Bucur, A., & Dorigo, W. (2020). Earth Observation for Agricultural Drought Monitoring in the Pannonian Basin (Southeastern Europe): Current State and Future Directions. Regional Environmental Change, 20(4), 123.
  • Dhu, T., Dunn, B., Lewis, B., Lymburner, L., Mueller, N., Telfer, E., … Phillips, C. (2017). Digital Earth Australia – Unlocking New Value from Earth Observation Data. Big Earth Data, 1(1–2), 64–74.
  • Dhu, T., Giuliani, J., Kavvada, J., Killough, A., Merodio, B., Minchin, P., & Ramage, S. (2019). National Open Data Cubes and Their Contribution to Country-Level Development Policies and Practices. Data, 4(4), 144.
  • Dwyer, J., Roy, D., Sauer, B., Jenkerson, C., Zhang, H., & Lymburner, L. (2018). Analysis Ready Data: Enabling Analysis of the Landsat Archive, August. https://doi.org/https://doi.org/10.20944/preprints201808.0029.v1
  • Ernst, S., Lymburner, L., & Sixsmith, J. (2018). Implications of Pixel Quality Flags on the Observation Density of a Continental Landsat Archive. Remote Sensing, 10(10), 1570.
  • Federal Office for the Environment FOEN. (2004). Biogeographical regions of Switzerland (CH). Retrieved from 07 July 2021. https://opendata.swiss/en/dataset/biogeographische-regionen-der-schweiz-ch
  • Fegraus, E. H., Zaslavsky, I., Whitenack, T., Dempewolf, J., Ahumada, J. A., Lin, K., & Andelman, S. J. (2012). Interdisciplinary Decision Support Dashboard: A New Framework for a Tanzanian Agricultural and Ecosystem Service Monitoring System Pilot. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(6), 1700–1708.
  • Fink, A. H., Brücher, T., Krüger, A., Leckebusch, G. C., Pinto, J. G., & Ulbrich, U. (2004). The 2003 European Summer Heatwaves and Drought –Synoptic Diagnosis and Impacts. Weather, 59(8), 209–216.
  • Fischer, A., Fickert, T., Schwaizer, G., Patzelt, G., & Groß, G. (2019). Vegetation Dynamics in Alpine Glacier Forelands Tackled from Space. Scientific Reports, 9(1), 1–13.
  • FOEN. (2021). Effects of Climate Change on Swiss Water Bodies. Bern, Switzerland: Author.
  • Fraisl, D., Campbell, J., See, L., Wehn, U., Wardlaw, J., Gold, M., Moorthy, I., Arias, R., Piera, J., Oliver, J. L., Maso, J., Penker, M., & Fritz, S. (2020, July). Mapping Citizen Science Contributions to the UN Sustainable Development Goals. Sustainability Science, https://doi.org/10.1007/s11625-020-00833-7
  • Fritz, S., See, L., Carlson, T., Haklay, M., Oliver, J. L., Fraisl, D., Mondardini, R., Brocklehurst, M., Shanley, L. A., Schade, S., Wehn, U., Abrate, T., Anstee, J., Arnold, S., Billot, M., Campbell, J., Espey, J., Gold, M., Hager, G., He, S., Hepburn, L., Hsu, A., Long, D., Masó, J., McCallum, I., Muniafu, M., Moorthy, I., Obersteiner, M., Parker, A. J., Weisspflug, M., & West, S. (2019). Citizen Science and the United Nations Sustainable Development Goals. Nature Sustainability, 2(10), 922–930.
  • Gao, B. (1996). NDWI—A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space. Remote Sensing of Environment, 58(3), 257–266.
  • Giuliani, G., Cazeaux, H., Burgi, P.-Y., Poussin, C., Richard, J.-P., & Chatenoux, B. (2021). SwissEnvEO: A FAIR National Environmental Data Repository for Earth Observation Open Science. Data Science Journal, 20(1), 22.
  • Giuliani, G., Chatenoux, B., Benvenuti, A., Lacroix, P., Santoro, M., & Mazzetti, P. (2020). Monitoring Land Degradation at National Level Using Satellite Earth Observation Time-Series Data to Support SDG15 – Exploring the Potential of Data Cube. Big Earth Data, 4(1), 1–20.
  • Giuliani, G., Chatenoux, B., De Bono, A., Rodila, D., Richard, J.-P., Allenbach, K., … Peduzzi, P. (2017). Building an Earth Observations Data Cube: Lessons Learned from the Swiss Data Cube (SDC) on Generating Analysis Ready Data (ARD). Big Earth Data, 1(1), 1–18.
  • Giuliani, G., Chatenoux, B., Honeck, E., & Richard, J.-P. (2018). Towards Sentinel-2 Analysis Ready Data: A Swiss Data Cube Perspective. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, 8659–8662. Valencia, Spain. https://doi.org/https://doi.org/10.1109/IGARSS.2018.8517954.
  • Giuliani, G., Egger, E., Italiano, J., Poussin, C., Richard, J.-P., & Chatenoux, B. (2020). Essential Variables for Environmental Monitoring: What Are the Possible Contributions of Earth Observation Data Cubes? Data, 5(4), 100.
  • Giuliani, G., Mazzetti, P., Santoro, M., Nativi, S., Van Bemmelen, J., Colangeli, G., & Lehmann, A. (2020). Knowledge Generation Using Satellite Earth Observations to Support Sustainable Development Goals (SDG): A Use Case on Land Degradation. International Journal of Applied Earth Observation and Geoinformation, 88(June), 102068.
  • Gobiet, A., Kotlarski, S., Beniston, M., Heinrich, G., Rajczak, J., & Stoffel, M. (2014). 21st Century Climate Change in the European Alps—A Review. Science of the Total Environment, 493(September), 1138–1151.
  • Gu, Y., Brown, J. F., Verdin, J. P., & Wardlow, B. (2007). A Five-Year Analysis of MODIS NDVI and NDWI for Grassland Drought Assessment over the Central Great Plains of the United States. Geophysical Research Letters, 34, 6.
  • Gu, Y., Hunt, E., Wardlow, B., Basara, J. B., Brown, J. F., & Verdin, J. (2008). Evaluation of MODIS NDVI and NDWI for Vegetation Drought Monitoring Using Oklahoma Mesonet Soil Moisture Data. Drought Mitigation Center Faculty Publications, January. https://digitalcommons.unl.edu/droughtfacpub/116.
  • Gulácsi, A., & Kovács, F. (2015). Drought Monitoring With Spectral Indices Calculated From Modis Satellite Images In Hungary. Journal of Environmental Geography, 8(3–4), 11–20.
  • Hirsch, R. M., & Slack, J. R. (1984). A Nonparametric Trend Test for Seasonal Data With Serial Dependence. Water Resources Research, 20(6), 727–732.
  • Ibrahim, E., Jiang, J., Lema, L., Barnabé, P., Giuliani, G., Lacroix, P., & Pirard, E. (2021). Cloud and Cloud-Shadow Detection for Applications in Mapping Small-Scale Mining in Colombia Using Sentinel-2 Imagery. Remote Sensing, 13(4), 736.
  • Jackson, T. J., Chen, D., Cosh, M., Li, F., Anderson, M., Walthall, C., … Hunt, E. R. (2004). Vegetation Water Content Mapping Using Landsat Data Derived Normalized Difference Water Index for Corn and Soybeans. Remote Sensing of Environment, 2002 Soil Moisture Experiment (SMEX02), 92(4), 475–482.
  • Javed, T., Li, Y., Rashid, S., Li, F., Hu, Q., Feng, H., … Pulatov, B. (2021). Performance and Relationship of Four Different Agricultural Drought Indices for Drought Monitoring in China’s Mainland Using Remote Sensing Data. Science of the Total Environment, 759(March), 143530.
  • Javed, T., Yao, N., Chen, X., Suon, S., & Li, Y. (2020). Drought Evolution Indicated by Meteorological and Remote-Sensing Drought Indices under Different Land Cover Types in China. Environmental Science and Pollution Research, 27(4), 4258–4274.
  • Javed, T., Zhang, J., Bhattarai, N., Sha, Z., Rashid, S., Yun, B., … Kamran, M. (2021). Drought Characterization across Agricultural Regions of China Using Standardized Precipitation and Vegetation Water Supply Indices. Journal of Cleaner Production, 313(September), 127866.
  • Jayawardhana, W. G., & Chathurange, V. M. (2020). Investigate the Sensitivity of the Satellite-Based Agricultural Drought Indices to Monitor the Drought Condition of Paddy and Introduction to Enhanced Multi-Temporal Drought Indices. Journal of Remote Sensing & GIS, 2(9), 1–11.
  • Jiao, W., Wang, L., & McCabe, M. F. (2021). Multi-Sensor Remote Sensing for Drought Characterization: Current Status, Opportunities and a Roadmap for the Future. Remote Sensing of Environment, 256(April), 112313.
  • Killough, B. (2018). Overview of the Open Data Cube Initiative. IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, 8629–8632. https://doi.org/https://doi.org/10.1109/IGARSS.2018.8517694.
  • Kueppers, L. M., Conlisk, E., Castanha, C., Moyes, A. B., Germino, M. J., de Valpine, P., … Mitton, J. B. (2017). Warming and Provenance Limit Tree Recruitment across and beyond the Elevation Range of Subalpine Forest. Global Change Biology, 23(6), 2383–2395.
  • Lacroix, P., Moser, F., Benvenuti, A., Piller, T., Jensen, D., Petersen, I., … Ray, N. (2019). MapX: An Open Geospatial Platform to Manage, Analyze and Visualize Data on Natural Resources and the Environment. SoftwareX, 9(January), 77–84.
  • Lee, S.-J., Cho, J., Hong, S., Ha, K.-J., Lee, H., & Lee, Y.-W. (2016). On the Relationships between Satellite-Based Drought Index and Gross Primary Production in the North Korean Croplands, 2000–2012. Remote Sensing Letters, 7(8), 790–799.
  • Lewis, A., Oliver, S., Lymburner, L., Evans, B., Wyborn, L., Mueller, N., Raevksi, G., Hooke, J., Woodcock, R., Sixsmith, J., Wu, W., Tan, P., Li, F., Killough, B., Minchin, S., Roberts, D., Ayers, D., Bala, B., Dwyer, J., Dekker, A., Dhu, T., Hicks, A., Ip, A., Purss, M., Richards, C., Sagar, S., Trenham, C., Wang, P., & Wang, L.-W. 2017. The Australian Geoscience Data Cube — Foundations and Lessons Learned. Remote Sensing of Environment. doi:https://doi.org/10.1016/j.rse.2017.03.015
  • Li, J., & Roy, D. P. (2017). A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring. Remote Sensing, 9(9), 902.
  • Magno, R., De Filippis, T., Di Giuseppe, D., Pasqui, M., Rocchi, L., & Gozzini, B. (2018). Semi-Automatic Operational Service for Drought Monitoring and Forecasting in the Tuscany Region. Geosciences, 8(2), 49.
  • Mann, H. B. (1945). Nonparametric Tests Against Trend. Econometrica, 13(3), 245–259.
  • Marusig, D., Petruzzellis, F., Tomasella, M., Napolitano, R., Altobelli, A., & Nardini, A. (2020). Correlation of Field-Measured and Remotely Sensed Plant Water Status as a Tool to Monitor the Risk of Drought-Induced Forest Decline. Forests, 11(1), 77.
  • Meroni, M., Fasbender, D., Rembold, F., Atzberger, C., & Klisch, A. (2019). Near Real-Time Vegetation Anomaly Detection with MODIS NDVI: Timeliness vs. Accuracy and Effect of Anomaly Computation Options. Remote Sensing of Environment, 221(February), 508–521.
  • MeteoSwiss. (2016a). Monthly and Yearly Mean Temperature: TabsM and TabsY. Author. https://www.meteoswiss.admin.ch/content/dam/meteoswiss/de/service-und-publikationen/produkt/raeumliche-daten-temperatur/doc/ProdDoc_TabsM.pdf
  • MeteoSwiss. (2016b). Monthly and Yearly Precipitation: RhiresM and RhiresY. Author. https://www.meteoswiss.admin.ch/home/climate/swiss-climate-in-detail/extreme-value-analyses/high-impact-precipitation-events/14-15-november-2002/precipitation-and-temperature.html?query=rhires
  • Metternicht, G., Mueller, N., & Lucas, R. (2020). Digital Earth for Sustainable Development Goals. In G. Huadong, M. F. Goodchild, & A. Annoni (Eds.), Manual of Digital Earth (pp. 443–471). Singapore: Springer. doi:https://doi.org/10.1007/978-981-32-9915-3_13
  • Mooney, H., Larigauderie, A., Cesario, M., Elmquist, T., Hoegh-Guldberg, O., Lavorel, S., … Yahara, T. (2009). Biodiversity, Climate Change, and Ecosystem Services. Current Opinion in Environmental Sustainability, 1(1), 46–54.
  • Nazarova, T., Martin, P., & Giuliani, G. (2020). Monitoring Vegetation Change in the Presence of High Cloud Cover with Sentinel-2 in a Lowland Tropical Forest Region in Brazil. Remote Sensing, 12(11), 1829.
  • Nolan, C., Overpeck, J. T., Allen, J. R. M., Anderson, P. M., Betancourt, J. L., Binney, H. A., Brewer, S., Bush, M. B., Chase, B. M., Cheddadi, R., Djamali M., Dodson, J., Edwards M. E., Gosling W. D., Haberle S., Hotchkiss, S. C., Huntley, B., Ivory, S. J., Kershaw, A. P., Kim, S. -H., Latorre, C., Leydet, M., Lézine, A. -M., Liu, K. -B., Liu, Y., Lozhkin, A. V., McGlone, M. S., Marchant, R. A., Momohara, A., Moreno, P. I., Müller, S., Otto-Bliesner, B. L., Shen, C., Stevenson, J., Takahara, H., Tarasov, P. E., Tipton, J., Vincens, A., Weng, C., Xu, Q., Zheng, Z., & Jackson, S. T. (2018). Past and Future Global Transformation of Terrestrial Ecosystems under Climate Change. Science, 361(6405), 920–923.
  • Oveisgharan, S., Haddad, Z., Turk, J., Rodriguez, E., & Li, L. (2018). Soil Moisture and Vegetation Water Content Retrieval Using QuikSCAT Data. Remote Sensing, 10(4), 636.
  • Peng, D., Zhang, B., Liu, L., Fang, H., Chen, D., Hu, Y., & Liu, L. (2012). Characteristics and drivers of global NDVI-based FPAR from 1982 to 2006. Global Biogeochemical Cycles, 26(3).
  • Peng, J., Wu, C., Zhang, X., Wang, X., & Gonsamo, A. (2019). Satellite Detection of Cumulative and Lagged Effects of Drought on Autumn Leaf Senescence over the Northern Hemisphere. Global Change Biology, 25(6), 2174–2188.
  • Poussin, C., Guigoz, Y., Palazzi, E., Terzago, S., Chatenoux, B., & Giuliani, G. (2019). Snow Cover Evolution in the Gran Paradiso National Park, Italian Alps, Using the Earth Observation Data Cube. Data, 4(4), 138.
  • Rebetez, M. (1999). Twentieth Century Trends in Droughts in Southern Switzerland. Geophysical Research Letters, 26(6), 755–758.
  • Sánchez-Ruiz, S., Piles, M., Sánchez, N., Martínez-Fernández, J., Vall-llossera, M., & Camps, A. (2014). Combining SMOS with Visible and near/Shortwave/Thermal Infrared Satellite Data for High Resolution Soil Moisture Estimates. Journal of Hydrology, Determination of Soil Moisture: Measurements and Theoretical Approaches, 516(August), 273–283.
  • Scherler, M., Remund, J., & Walthert, L. (2016). Régime Hydrique Des Forêts et Accroissement de La Sécheresse. https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A10629/.
  • Schmucki, E., Marty, C., Fierz, C., Weingartner, R., & Lehning, M. (2017). Impact of Climate Change in Switzerland on Socioeconomic Snow Indices. Theoretical and Applied Climatology, 127(3–4), 875–889.
  • Schuldt, B., Buras, A., Arend, M., Vitasse, Y., Beierkuhnlein, C., Damm, A., Gharun, M., Grams, T. E. E., Hauck, M., Hajek, P., Hartmann, H., Hiltbrunner, E., Hoch, G., Holloway-Phillips, M., Körner, C., Larysch, E., Lübbe, T., Nelson, D. B., Rammig, A., Rigling, A., Rose, L., Ruehr, N. K., Schumann, K., Weiser, F., Werner, C., Wohlgemuth, T., Zang, C. S., Kahmen, A. (2020). A First Assessment of the Impact of the Extreme 2018 Summer Drought on Central European Forests. Basic and Applied Ecology, 45(June), 86–103.
  • Serrano, J., Shahidian, S., & Marques Da Silva, J. (2019). Evaluation of Normalized Difference Water Index as a Tool for Monitoring Pasture Seasonal and Inter-Annual Variability in a Mediterranean Agro-Silvo-Pastoral System. Water, 11(1), 62.
  • Small, D., Rohner, C., Miranda, N., Rüetschi, M., & Schaepman, M. E. (2021). Wide-Area Analysis-Ready Radar Backscatter Composites. IEEE Transactions on Geoscience and Remote Sensing, 1–14. doi:https://doi.org/10.1109/TGRS.2021.3055562
  • Sun, H., Zhao, X., Chen, Y., Gong, A., & Yang, J. (2013). A New Agricultural Drought Monitoring Index Combining MODIS NDWI and Day–Night Land Surface Temperatures: A Case Study in China. International Journal of Remote Sensing, 34(24), 8986–9001.
  • Svoboda, M., & Fuchs, B. (2016). Handbook of Drought Indicators and Indices. Integrated Drought Management Tools and Guidelines Series 2. Geneva: World Meteorological Organization. https://www.droughtmanagement.info/literature/GWP_Handbook_of_Drought_Indicators_and_Indices_2016.pdf.
  • Truckenbrodt, J., Freemantle, T., Williams, C., Jones, T., Small, D., Dubois, C., … Giuliani, G. (2019). Towards Sentinel-1 SAR Analysis-Ready Data: A Best Practices Assessment on Preparing Backscatter Data for the Cube. Data, 4(3), 93.
  • Trujillo, E., Molotch, N. P., Goulden, M. L., Kelly, A. E., & Bales, R. C. (2012). Elevation-Dependent Influence of Snow Accumulation on Forest Greening. Nature Geoscience, 5(10), 705–709.
  • Tucker, C. J. (1980). Remote Sensing of Leaf Water Content in the near Infrared. Remote Sensing of Environment, 10(1), 23–32.
  • United Nations. (2015). Transforming Our World: The 2030 Agenda for Sustainable Development. New York. https://sustainabledevelopment.un.org/post2015/transformingourworld/publication
  • United Nations Environment Programme. (2021). Making Peace with Nature: A Scientific Blueprint to Tackle the Climate, Biodiversity and Pollution Emergencies. Nairobi: UNEP.
  • Van Ginkel, K. C. H., Hoekstra, A. Y., Buurman, J., & Hogeboom, R. J. (2018). Urban Water Security Dashboard: Systems Approach to Characterizing the Water Security of Cities. Journal of Water Resources Planning and Management, 144(12), 04018075.
  • Vicente-Serrano, S. M., Begueria, S., Gimeno, L., Eklundh, L., Giuliani, G., Weston, D., El Kenawy, A., et al. (2012). Challenges for drought mitigation in africa: the potential use of geospatial data and drought information systems. Applied Geography, 34, 471–486.
  • Vittoz, P., Cherix, D., Gonseth, Y., Lubini, V., Maggini, R., Zbinden, N., & Zumbach, S. (2013). Climate Change Impacts on Biodiversity in Switzerland: A Review. Journal for Nature Conservation, 21(3), 154–162.
  • Wang, X., Fuller, D. O., da Silveira, L., O’Reilly Sternberg, L., & Miralles-Wilhelm, F. (2011). Foliar Nutrient and Water Content in Subtropical Tree Islands: A New Chemohydrodynamic Link between Satellite Vegetation Indices and Foliar Δ15N Values. Remote Sensing of Environment, 115(3), 923–930.
  • West, H., Quinn, N., & Horswell, M. (2019). Remote Sensing for Drought Monitoring & Impact Assessment: Progress, Past Challenges and Future Opportunities. Remote Sensing of Environment, 232(October), 111291.
  • Whitcraft, A. K., Becker-Reshef, I., Justice, C. O., Gifford, L., Kavvada, A., & Jarvis, I. (2019). No Pixel Left behind: Toward Integrating Earth Observations for Agriculture into the United Nations Sustainable Development Goals Framework. Remote Sensing of Environment, 235(December), 111470.
  • WMO. (2012). Standardized Precipitation Index User Guide. Geneva, Switzerland: Author. https://public.wmo.int/en/resources/library/standardized-precipitation-index-user-guide
  • Wulder, M. A., Ortlepp, S. M., White, J. C., & Maxwell, S. (2008). Evaluation of Landsat-7 SLC-off Image Products for Forest Change Detection. Canadian Journal of Remote Sensing, 34(2), 93–99.
  • Yoccoz, N. G., Delestrade, A., & Loison, A. (2010). Impact of Climatic Change on Alpine Ecosystems: Inference and Prediction. Journal of Alpine Research | Revue De Géographie Alpine, 98–4(December). doi:https://doi.org/10.4000/rga.1293
  • Zemp, M., Paul, F., Hoelzle, M., Haeberli, W. (2008). Glacier Fluctuations in the European Alps, 1850–2000: An Overview and Spatio-Temporal Analysis of Available Data. In Orlove, B. et al. (Eds.), Darkening Peaks: Glacier Retreat, Science, and Society (pp. 152–167). Berkeley, US: University of California Press. doi:https://doi.org/10.5167/uzh-9024
  • Zhao, J., Huang, S., Huang, Q., Wang, H., Leng, G., & Fang, W. (2020). Time-Lagged Response of Vegetation Dynamics to Climatic and Teleconnection Factors. CATENA, 189(June), 104474.
  • Zhou, Y., Xiao, X., Zhang, G., Wagle, P., Bajgain, R., Dong, J., Jin, C., Basara, J. B., Anderson, M. C., Hain, C., Otkin, J. A. (2017). Quantifying Agricultural Drought in Tallgrass Prairie Region in the U.S. Southern Great Plains through Analysis of a Water-Related Vegetation Index from MODIS Images. Agricultural and Forest Meteorology, 246(November), 111–122.
  • Zhu, Z., Wulder, M. A., Roy, D. P., Woodcock, C. E., Hansen, M. C., Radeloff, V. C., Healey, S. P., Schaaf, C., Hostert, P., Strobl, P., Pekel, J. -F., Lymburner, L., Pahlevan, N., Scambos, T. A. (2019). Benefits of the Free and Open Landsat Data Policy. Remote Sensing of Environment, 224(April), 382–385.