During the last decade, the State of Texas, USA has suffered from several severe to extreme agricultural droughts,
which caused significant decreases in cotton yields, especially in 2006, 2008, 2009 and 2011. Texas alone has been
accounted for approximately 50% of the acres of upland cotton planted in the U.S. In the event of an agricultural
drought solely in Texas, the total cotton production in the U.S. would be greatly reduced. This paper discusses the
detection of agricultural droughts over cotton fields in Texas between 2000 and 2011 by using freely available
remote sensing data and the implications of these drought events on cotton yield and cotton price. Remotely sensed
vegetation condition indices, such as the normalized difference vegetation index (NDVI) and the vegetation
condition index (VCI), are prominent indictors of vegetation health conditions. The temperature condition index
(TCI) is a supplement to the vegetation indices and provides general information about thermal conditions in an area
of interest. Because agricultural drought will cause stress on vegetation, remotely sensed vegetation condition
indices along with the temperature index can be used to monitor agricultural droughts. Multiple agricultural drought
maps have been generated by using those indices for the years from 2000 to 2011. We found that the northern,
western and northwestern Texas were exposed to severe to exceptional droughts during the most active planting
season of the upland cotton. In comparison to our findings, the U.S. Drought Monitor (USDM) operated by NOAA
reported extreme to exceptional droughts in the northern, western and northwestern parts of Texas for the same
periods. However, our agricultural drought maps and USDM maps did not agree in term of the spatial distribution of
agricultural droughts in other parts of Texas. In addition, when night temperature products derived from the MODIS
instrument onboard Aqua satellite were added into the agricultural drought monitoring algorithm, they
unrealistically reduced the intensity of agricultural droughts. This study suggests that freely available satellite data
can be used to monitor agricultural drought events with satisfactory result, and such information can be further used
to predict the crop yields and prices.