## 4 Conclusions
\begin{table}
\begin{tabular}{c c c} \hline
**BGW** & **2009–2010** & **2010–2011** \\ \hline \multicolumn{4}{c}{**Houston Site**} \\ \hline \(+++\) & 31.1\% R to A; F to A; A to F & 0.9\% R to A; F to A; A to R \\ \(-++\) & 21.3\% R to F; R to A; U to F & 2.6\% R to A; R to F; A to F \\ \(+-+\) & 0.3\% A to U; F to U; R to U & 0.3\% R to U; F to U; A to U \\ \(--+\) & 2.4\% A to F; A to U; F to U & 2.1\% A to F; A to U; F to U \\ \(++-\) & 15.6\% F to A; U to F; U to A & 3.7\% F to A; U to A; U to R \\ \(-+-\) & 0.9\% U to A; U to R; U to F & 0.1\% U to A; U to R; U to F \\ \(+--\) & 23.6\% F to A; F to R; A to R & 65.2\% F to R; A to R; F to A \\ \(---\) & 4.9\% A to R; A to F; F to A & 25.2\% A to R; F to R; F to A \\ \hline \multicolumn{4}{c}{**South Texas Site**} \\ \hline \(++\) & 8.4\% R to A; U to A; R to A & 0.8\% R to A; U to A; R to U \\ \(-++\) & 2.6\% R to A; U to A; U to F & 0.7\% R to A; U to A; R to A \\ \(+-+\) & 0.1\% R to U; F to U; A to U & 0.1\% R to U; F to U; A to U \\ \(--+\) & 2.2\% A to W; A to U; U to W & 0.4\% A to R; R to U; A to U \\ \(++-\) & 7.6\% R to A; R to U; U to A & 1.1\% U to A; F to R; W to U \\ \(-+-\) & 0.1\% R to U; U to R; U to W & 0.1\% U to R; R to U; F to U \\ \(+--\) & 63.7\% A to R; W to F; U to R & 91.4\% A to R; A to U; F to R \\ \(---\) & 15.4\% A to R; A to F; F to A & 5.5\% A to R; A to U; F to R \\ \hline \end{tabular}
\end{table} 
Table 4: Top three ‘from-to’ land use/cover changes from threshold TCT for the Houston site and South Texas site (refer to Table 3 for key). established image analysis statistics. Our methodology measures sudden dryness using change vector analysis of NDVI-NDMI, and the brightness, greenness, and wetness variables from tasseled cap. Together these statistics measure land use/cover changes during severe sudden short-term drought events by calculating not only vegetation and bare soil indices, but also determine the intensity of change (magnitude) and the type of change (direction). Although these image-processing techniques have long been available, they have as yet been applied to assessing drought conditions in land use/cover changes. One reason may be that sudden dryness is not considered serious enough for multiple studies. Another reason may be that these techniques are underrated. With increasing fluctuations in weather linked primarily to climate change, research on precise measurements of sudden aridity and prolonged drought are gaining prominence for assessing ecosystem disturbances, agricultural loss, and even threat to life, especially if dryness leads to more fires. As well, in terms of underrated techniques, the NDVI-NDMI combination continues to produce reliable and important measures of vegetation and moisture. So too tasseled cap transforms that measure bare soil and vegetation. In terms of change vector, we have included an improvement 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. Our test sites are from satellite sensor images taken of notoriously high frequency sudden short-term drought events over the southern state of Texas. A 'from-to' land use/cover change assessment was made for each direction class to discern any patterns with any particular change directions as a result of severe aridity. Overall accuracies and Kappa coefficients for both the Houston and South Texas sites were found to be higher for the NDVI-NDMI and TCT calculations when compared with the NDVI-BI results. CVA was performed on NDVI and NDMI with change direction classes as expected when predicting drought. However, the relationships between TCT brightness, greenness and wetness and their ability to detect change was more difficult to determine by their type of change in each of the directions, and hence they may be context dependent. In terms of short-term droughts in humid subtropical climatic regions, such as the south and southeast United States, some interesting change directions were evident.