Spatially-explicit depictions of plant productivity over large areas are critical to monitoring landscapes in highly heterogeneous arid ecosystems. Applying radiometric change detection techniques we sought to determine whether: (1) differences between pre- and post-growing season spectral vegetation index values effectively identify areas of significant change in vegetation; and (2) areas of significant change coincide with altered ecological states. We differenced NDVI values, standardized difference values to Z-scores to identify areas of significant increase and decrease in NDVI, and examined the ecological states associated with these areas. The vegetation index differencing method and translation of growing season NDVI to Z-scores permit examination of change over large areas and can be applied by non-experts. This method identified areas with potential for vegetation/ecological state transition and serves to guide field reconnaissance efforts that may ultimately inform land management decisions for millions of acres of federal lands.
References
[1]
Overpeck, J.; Udall, B. Dry times ahead. Science 2010, 328, 1642–1643, doi:10.1126/science.1186591. 20576877
[2]
Woodhouse, C.A.; Overpeck, J.T. 2000 years of drought variability in the central United States. Bull. Amer. Meteorol. Soc 1998, 79, 2693–2714, doi:10.1175/1520-0477(1998)079<2693:YODVIT>2.0.CO;2.
[3]
Joyce, L.A. An Analysis of the Range Forage Situation in the United States: 1989–2040. General Technical Report RM-180; US Department of Agriculture, Forest Service, Rocky Mountain Range and Forest Experiment Station: Fort Collins, CO, USA, 1989; p. 90.
[4]
Briske, D.D.; Fuhlendorf, S.D.; Smeins, F.E. State-and-transition models, thresholds, and rangeland health: A synthesis of ecological concepts and perspectives. Rangel. Ecol. Manage 2005, 58, 1–10, doi:10.2111/1551-5028(2005)58<1:SMTARH>2.0.CO;2.
[5]
Bestelmeyer, B.T.; Brown, J.R.; Havstad, K.M.; Alexander, R.; Chavez, G.; Herrick, J.E. Development and use of state-and-transition models for rangelands. J. Range Manage 2003, 56, 114–126, doi:10.2307/4003894.
[6]
Bestelmeyer, B.T.; Tugel, A.J.; Peacock, G.L.; Robinett, D.G.; Shaver, P.L.; Brown, J.R.; Herrick, J.E.; Sanchez, H.; Havstad, K.M. State-and-transition models for heterogeneous landscapes: A strategy for development and application. Rangel. Ecol. Manage 2009, 62, 1–15, doi:10.2111/08-146.
[7]
Briske, D.D.; Bestelmeyer, B.T.; Stringham, T.K.; Shaver, P.L. Recommendations for development of resilience-based state-and-transition models. Rangel. Ecol. Manage 2008, 61, 359–367, doi:10.2111/07-051.1.
Nelson, R.F. Detecting forest canopy change due to insect activity using Landsat MSS. Photogramm. Eng. Remote Sensing 1983, 49, 1303–1314.
[10]
Alphan, H. Comparing the utility of image algebra operations for characterizing landscape changes: The case of the Mediterranean coast. J. Environ. Manage 2011, 92, 2961–2971, doi:10.1016/j.jenvman.2011.07.009. 21820236
[11]
Singh, A. Review article: Digital change detection techniques using remotely-sensed data. Int. J. Remote Sens 1989, 10, 989–1003, doi:10.1080/01431168908903939.
Tucker, C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ 1979, 8, 127–150, doi:10.1016/0034-4257(79)90013-0.
[14]
Brown, D.E. Biotic Communities: Southwestern United States and Northwestern Mexico; University of Utah Press: Salt Lake City, UT, USA, 1994; p. 342.
[15]
Chavez, P.S., Jr. Image-based atmospheric corrections--revisited and improved. Photogramm. Eng. Remote Sensing 1996, 62, 1025–1036.
[16]
Peters, A.J.; Walter-Shea, E.A.; Ji, L.; Vina, A.; Hayes, M.; Svoboda, M.D. Drought monitoring with NDVI-based standardized vegetation index. Photogramm. Eng. Remote Sensing 2002, 68, 71–75.
[17]
National Resources Conservation Service. Land Resource Regions and Major Land Resource Areas of the United States, the Caribbean, and the Pacific Basin. USDA Arigcultural Handbook 296; National Resource Conservation Service, USDA: Washington, DC, USA, 2006; p. 682.
[18]
USDA-NRCS. Ecological Site Description: Clay Loam Upland (R041XA109AZ); National Resource Conservation Service, USDA: Washington, DC, USA, 2005.
[19]
Sheley, R.L.; James, J.J.; Rinella, M.J.; Bluemthal, D.; di Tomaso, J.M. Invasive Plant Management on Anticipated Conservation Benefits: A Scientific Assessment. In Conservation Benefits of Rangeland Practices—Assessment, Recommendations, and Knowledge Gaps; Briske, D.D., Ed.; US Department of Agriculture Natural Resource Conservation Service: Washington, DC, USA, 2011.
[20]
USDA-NRCS. Ecological Site Description: Loamy Bottom (RO41XA114AZ); National Resource Conservation Service, USDA: Washington, DC, USA, 2005.
[21]
Ludwig, J.A.; Bastin, G.N.; Wallace, J.F.; McVicar, T.R. Assessing landscape health by scaling with remote sensing: When is it not enough? Landscape Ecol 2007, 22, 163–169, doi:10.1007/s10980-006-9038-6.
[22]
Forbis, T.A.; Provencher, L.; Turner, L.; Medlyn, G.; Thompson, J.; Jones, G. A method for landscape-scale vegetation assessment: Application to great basin rangeland ecosystems. Rangel. Ecol. Manage 2007, 60, 209–217, doi:10.2111/1551-5028(2007)60[209:AMFLVA]2.0.CO;2.
[23]
Roy, D.P.; Ju, J.C.; Kline, K.; Scaramuzza, P.L.; Kovalskyy, V.; Hansen, M.; Loveland, T.R.; Vermote, E.; Zhang, C.S. Web-enabled Landsat Data (WELD): Landsat ETM plus composited mosaics of the conterminous United States. Remote Sens. Environ 2010, 114, 35–49, doi:10.1016/j.rse.2009.08.011.
[24]
Coppin, P.; Jonckheere, I.; Nackaerts, K.; Muys, B.; Lambin, E. Digital change detection methods in ecosystem monitoring: A review. Int. J. Remote Sens 2004, 25, 1565–1596, doi:10.1080/0143116031000101675.
[25]
Karl, J.W.; Herrick, J.E.; Browning, D.M. A vision for rangeland management based on best available knowledge and information. Rangel. Ecol. Manage 2012, 65, 638–646, doi:10.2111/REM-D-12-00021.1.
[26]
Briske, D.D.; Fuhlendorf, S.D.; Smeins, F.E. A unified framework for assessment and application of ecological thresholds. Rangel. Ecol. Manage 2006, 59, 225–236, doi:10.2111/05-115R.1.
[27]
Wilson, J.R.J.; Blackmon, C.; Spann, G.W. Land use change detection using Landsat data. Remote Sens. Earth Resour 1977, 5, 79–91.