Abstract
Sudden short-term severe droughts have major impacts on ecosystem balance. Synoptic and replicable measurements from remotely sensed data are essential for calculating changes to land use/cover caused by severe drought conditions. In the US, Texas experienced a particularly severe drought in 2011, which adversely affected forest and grassland ecosystems in addition to $7.62 billion of agricultural loss. To assess the extent and severity of the drought we use satellite sensor data and image processing techniques to measure changes in land use/cover. Our methodology uses change vector analysis (CVA), the normalized difference vegetation index, the normalized difference moisture index, and three variables-brightness, greenness, and wetness-extracted from tasseled cap transforms (TCT). All are established techniques in remote sensing but have as yet been applied in combination to measure land use/cover changes affected by intense short-term drought conditions. Our objective is to calculate not only vegetation and bare soil indices, but also the intensity of change (magnitude) and the type of change (direction). For CVA direction, we include an improved methodology using the arctangent function based on two arguments, ATAN2 which produces results in all four possible quadrants, and complete characterization of all possible change directions. The three variables of TCT are applied to CVA magnitude and direction using vectors in three dimensions, resulting in eight change categories. Our results are based on Landsat TM sensor data for the years 2009, 2010 and 2011, which represent a short period of severe drought, above average precipitation, and severe drought respectively, for two study sites in Texas. Results indicate that land use/cover changes were affected by both an increase in precipitation in 2010 as well as a considerable decrease of precipitation in 2011 resulting in the devastating sudden drought.
Highlights
Sudden short periods of severe drought can be disruptive for both natural ecosystems and human societies
From Google Earth, overall accuracy and Kappa coefficients for both the Houston and South Texas sites were found to be higher for the normalized difference vegetation index (NDVI)-normalized difference moisture index (NDMI) and tasseled cap transforms (TCT) calculations when compared with NDVI-bare soils index (BI)
For the South Texas site, overall accuracies are much lower, ranging between 58% and 65%, with the Kappa coefficients, lower, between 43% and 51%. These accuracies are higher than the NDVI-BI calculation, which has an overall accuracy and Kappa coefficient for the first and second year pairs of 73% and 21%, and 71% and 22% respectively
Summary
Sudden short periods of severe drought can be disruptive for both natural ecosystems and human societies. They adversely affect water resources, agricultural production, and raise the risk of fire. According to the Texas AgriLife Extension Service, the drought caused $7.62 billion in agricultural loss (43% of the average value of agricultural production over the previous four years). In subsequent years as water demand rose, changes in hydro-meteorological variables due to climate change exacerbated the impacts of future droughts [2,3]. A period of drought is monitored using in situ meteorological data from weather stations. Due to cost constraints and logistical difficulties of locating monitoring stations at multiple sites, in situ variables are insufficient for measuring spatial and temporal extensiveness of droughts. Remotely sensed data are available in variable spatial resolutions and conducive to digital processing [4]
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