Potential of Landsat spectral indices in regard to the detection of forest health changes due to drought effects

https://doi.org/10.17221/137/2018-JFSCitation:Hais M., Neudertová Hellebrandová K., Šrámek V. (2019): Potential of Landsat spectral indices in regard to the detection of forest health changes due to drought effects. J. For. Sci., 65: 70-78.
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Because of climatic variability that has been increasing in last decades a higher drought risk seriously influences the forest vitality from regional to global scale. Despite there are of many studies that describe the spectral response of forest stands to the water stress, there is still a lack of information concerning the full understanding of forest reaction to the water deficiency over a longer time period. We hypothesize that the various severity and/or frequency of drought periods will result in different spectral responses of forest stands. The forest response was detected using two spectral vegetation indices (normalized difference moisture index – NDMI, wetness) which are widely used for the detection of forest health changes. These indices were calculated on the basis of Landsat (TM, ETM+ and OLI) imagery which includes 105 scenes from the 2005–2016 period. The area of our interest includes 300 forest stands (dominated with Norway spruce) in the Czech Republic, Moravia. These stands were identified as damaged by drought that occurred during the 2012–2017 period. To document the climatic water deficiency, two climatic indices were calculated (AWBPE, standardized precipitation evapotranspiration index). Despite high correlation of both spectral indices, the NDMI has high sensitivity to the drought events. However, both indices significantly decreased in reaction to the drought events. In case of the 2012 drought event the decrease was one year delayed, probably due to the lower severity of drought effect. The both groups of spectral and climatic indices bring valuable information in regard to the description and understanding of drought effect on the spruce forest stands.

Aakala Tuomas, Kuuluvainen Timo, Wallenius Tuomo, Kauhanen Heikki (2011): Tree mortality episodes in the intact Picea abies-dominated taiga in the Arkhangelsk region of northern European Russia. Journal of Vegetation Science, 22, 322-333  https://doi.org/10.1111/j.1654-1103.2010.01253.x
Allen Richard G., Clemmens Albert J., Burt Charles M., Solomon Ken, O’Halloran Tim (2005): Prediction Accuracy for Projectwide Evapotranspiration Using Crop Coefficients and Reference Evapotranspiration. Journal of Irrigation and Drainage Engineering, 131, 24-36  https://doi.org/10.1061/(ASCE)0733-9437(2005)131:1(24)
Assal Timothy J., Anderson Patrick J., Sibold Jason (2016): Spatial and temporal trends of drought effects in a heterogeneous semi-arid forest ecosystem. Forest Ecology and Management, 365, 137-151  https://doi.org/10.1016/j.foreco.2016.01.017
Baig Muhammad Hasan Ali, Zhang Lifu, Shuai Tong, Tong Qingxi (2014): Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance. Remote Sensing Letters, 5, 423-431  https://doi.org/10.1080/2150704X.2014.915434
Bonneau L.R., Shields K.S., Civco D.L. (1999): Using satellite images to classify and analyze the health of hemlock forests infested by the hemlock woolly adelgid. Biological Invasions, 1: 255–267. https://doi.org/10.1023/A:1010021629127
Cohen W.B. (1995): Response of vegetation indices to changes in three measures of leaf water stress. Photogrammetric Engineering and Remote Sensing, 57: 195–202.
Crist E.P., Cicone R.C. (1984): Application of the tasseled cap concept to simulated thematic mapper data. Photogrammetric Engineering and Remote Sensing, 50: 343–352.
Hansen J., Ruedy R., Sato M., Lo K. (2010): GLOBAL SURFACE TEMPERATURE CHANGE. Reviews of Geophysics, 48, -  https://doi.org/10.1029/2010RG000345
Hartmann Henrik, Ziegler Waldemar, Kolle Olaf, Trumbore Susan (2013): Thirst beats hunger - declining hydration during drought prevents carbon starvation in Norway spruce saplings. New Phytologist, 200, 340-349  https://doi.org/10.1111/nph.12331
HEALEY S, COHEN W, ZHIQIANG Y, KRANKINA O (2005): Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection. Remote Sensing of Environment, 97, 301-310  https://doi.org/10.1016/j.rse.2005.05.009
Hlásny Tomáš, Barka Ivan, Sitková Zuzana, Bucha Tomáš, Konôpka Milan, Lukáč Martin (2015): MODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests. Annals of Forest Science, 72, 109-125  https://doi.org/10.1007/s13595-014-0404-2
Huang C., Wylie B., Yang L., Homer C., Zylstra G. (2010): Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance. International Journal of Remote Sensing, 23, 1741-1748  https://doi.org/10.1080/01431160110106113
Jin Suming, Sader Steven A. (2005): Comparison of time series tasseled cap wetness and the normalized difference moisture index in detecting forest disturbances. Remote Sensing of Environment, 94, 364-372  https://doi.org/10.1016/j.rse.2004.10.012
Kauth R.J., Thomas G.S. (1976): The tasseled cap – a graphic description of the spectral-temporal development of agricultural crops as seen in Landsat. In: Swain P. H.: Proceedings of the Symposium on Machine Processing of Remotely Sensed Data, West Lafayette, June 29–July 1, 1976: 41–51.
Kennedy Robert E, Andréfouët Serge, Cohen Warren B, Gómez Cristina, Griffiths Patrick, Hais Martin, Healey Sean P, Helmer Eileen H, Hostert Patrick, Lyons Mitchell B, Meigs Garrett W, Pflugmacher Dirk, Phinn Stuart R, Powell Scott L, Scarth Peter, Sen Susmita, Schroeder Todd A, Schneider Annemarie, Sonnenschein Ruth, Vogelmann James E, Wulder Michael A, Zhu Zhe (2014): Bringing an ecological view of change to Landsat-based remote sensing. Frontiers in Ecology and the Environment, 12, 339-346  https://doi.org/10.1890/130066
Lambert N. J., Ardo J., Rock B. N., VOGELMANN J. E. (2007): Spectral characterization and regression-based classification of forest damage in Norway spruce stands in the Czech Republic using Landsat Thematic Mapper data. International Journal of Remote Sensing, 16, 1261-1287  https://doi.org/10.1080/01431169508954476
Lubojacký J. (2013): Škodliví činitelé v lesích Moravskoslezského kraje v letech 2002–2012. Lesnická práce, 92: 366–367.
McDowell N., Pockman W.T., Allen C.D., Breshears D.D., Cobb N., Kolb T., Plaut J., Sperry J., West A., Williams D.G., Yepez E.A. (2008): Mechanisms of plant survival and mortality during drought: Why do some plants survive while others succumb to drought? New Phytologist, 178: 719–739.
McKee T.B., Doesken N.J., Kleist J. (1993): The relationship of drought frequency and duration to time scales. In: 8th Conference on Applied Climatology, Boston, Jan 17–23, 1993: 179–184.
Nicolai-Shaw Nadine, Zscheischler Jakob, Hirschi Martin, Gudmundsson Lukas, Seneviratne Sonia I. (2017): A drought event composite analysis using satellite remote-sensing based soil moisture. Remote Sensing of Environment, 203, 216-225  https://doi.org/10.1016/j.rse.2017.06.014
Norman Steven P., Koch Frank H., Hargrove William W. (2016): Review of broad-scale drought monitoring of forests: Toward an integrated data mining approach. Forest Ecology and Management, 380, 346-358  https://doi.org/10.1016/j.foreco.2016.06.027
Palmer W.C. (1965): Meteorological Droughts. Research Paper No. 45. Washington, D.C., U.S. Department of Commerce, Weather Bureau: 58.
Rock B.N., Williams D.L., Vogelmann J.E. (1985): Field and airborne spectral characterization of suspected acid deposition damage in red spruce (Picea rubens) from Vermont. In: Proceedings: Symposia on Machine Processing of Remotely Sensed Data, West Lafayette, June 25–27, 1985: 71–81.
Sandholt Inge, Rasmussen Kjeld, Andersen Jens (2002): A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment, 79, 213-224  https://doi.org/10.1016/S0034-4257(01)00274-7
Skakun Robert S., Wulder Michael A., Franklin Steven E. (2003): Sensitivity of the thematic mapper enhanced wetness difference index to detect mountain pine beetle red-attack damage. Remote Sensing of Environment, 86, 433-443  https://doi.org/10.1016/S0034-4257(03)00112-3
Štěpánek Petr, Trnka Miroslav, Chuchma Filip, Zahradníček Pavel, Skalák Petr, Farda Aleš, Fiala Rostislav, Hlavinka Petr, Balek Jan, Semerádová Daniela, Možný Martin (2018): Drought Prediction System for Central Europe and Its Validation. Geosciences, 8, 104-  https://doi.org/10.3390/geosciences8040104
Vicente-Serrano Sergio M., Beguería Santiago, López-Moreno Juan I. (2010): A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. Journal of Climate, 23, 1696-1718  https://doi.org/10.1175/2009JCLI2909.1
José Vidal-Macua Juan, Ninyerola Miquel, Zabala Alaitz, Domingo-Marimon Cristina, Pons Xavier (2017): Factors affecting forest dynamics in the Iberian Peninsula from 1987 to 2012. The role of topography and drought. Forest Ecology and Management, 406, 290-306  https://doi.org/10.1016/j.foreco.2017.10.011
Wulder M.A., Skakun R.S., Kurz W.A., White J.C. (2004): Estimating time since forest harvest using segmented Landsat ETM+ imagery. Remote Sensing of Environment, 93, 179-187  https://doi.org/10.1016/j.rse.2004.07.009
Wulder Michael A., Masek Jeffrey G., Cohen Warren B., Loveland Thomas R., Woodcock Curtis E. (2012): Opening the archive: How free data has enabled the science and monitoring promise of Landsat. Remote Sensing of Environment, 122, 2-10  https://doi.org/10.1016/j.rse.2012.01.010
Zhang Lifu, Jiao Wenzhe, Zhang Hongming, Huang Changping, Tong Qingxi (2017): Studying drought phenomena in the Continental United States in 2011 and 2012 using various drought indices. Remote Sensing of Environment, 190, 96-106  https://doi.org/10.1016/j.rse.2016.12.010
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