Sixteen Years of Agricultural Drought Assessment of the BioBío Region in Chile Using a 250 m Resolution Vegetation Condition Index (VCI)

Abstract

Drought is one of the most complex natural hazards because of its slow onset and long-term impact; it has the potential to negatively affect many people. There are several advantages to using remote sensing to monitor drought, especially in developing countries with limited historical meteorological records and a low weather station density. In the present study, we assessed agricultural drought in the croplands of the BioBío Region in Chile. The vegetation condition index (VCI) allows identifying the temporal and spatial variations of vegetation conditions associated with stress because of rainfall deficit. The VCI was derived at a 250 m spatial resolution for the 2000-2015 period with the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 product. We evaluated VCI for cropland areas using the land cover MCD12Q1 version 5.1 product and compared it to the in situ Standardized Precipitation Index (SPI) for six-time scales (1-6 months) from 26 weather stations. Results showed that the 3-month SPI (SPI-3), calculated for the modified growing season (November-April) instead of the regular growing season (September-April), has the best Pearson correlation with VCI values with an overall correlation of 0.63 and between 0.40 and 0.78 for the administrative units. These results show a very short-term vegetation response to rainfall deficit in September, which is reflected in the vegetation in November, and also explains to a large degree the variation in vegetation stress. It is shown that for the last 16 years in the BioBío Region we could identify the 2007/2008, 2008/2009, and 2014/2015 seasons as the three most important drought events; this is reflected in both the overall regional and administrative unit analyses. These results concur with drought emergencies declared by the regional government. Future studies are needed to associate the remote sensing values observed at high resolution (250 m) with the measured crop yield to identify more detailed individual crop responses.

Capability of Remotely Sensed Drought Indices for Representing the Spatio–Temporal Variations of the Meteorological Droughts in the Yellow River Basin

“…Kogan considered that the Vegetation Condition Index (VCI) is capable of monitoring drought and providing accurate drought information under different ecological environmental conditions in the United States. The VCI is suitable for monitoring the interannual dry-wet conditions and can eliminate the effects of climatic conditions, soil type, and topography, allowing comparison between different regions [15,16]. The Temperature Condition Index (TCI) is defined by the principle of elevated temperature and deficient water, and vegetation canopy or soil surface temperature increases with the rise of water stress.…”

Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective

“…The main growing season from October to March was identified as the most important time for farmers in Eastern Cape. Figure 4a shows the classification of the VCI over the main growing season on a monthly basis referring to the drought severity classification scheme described in Table 1 [64][65][66] over a normal year, i.e., 2011/2012. D0 conditions, indicating no drought, can be found throughout the season over most of the province.…”

“…The classification scheme to indicate different stages of drought hazard severity using VCI is shown in Table 1 [64][65][66]. VCI analysis was conducted based on all images available over the growing seasons within the observation period between 2000 and 2016 to detect possible drought hazard severity during the observation period as well as the correlation between VCI and rainfall to identify the dependency of vegetation condition on precipitation within the region.…”

Monitoring of Drought Condition and Risk in Bangladesh Combined Data From Satellite and Ground Meteorological Observations

“…where, NDVI j is the average NDVI value of the pixels during a specific period, and NDVI max and NDVI min are the maximum and minimum values of NDVI during that particular time [60], [61]. Ecosystem and weather are two environmental parameters which characterize by NDVI where, the former one explains the long-term change in the environment, and the later one explains inter-annual variation in each ecosystem [62], [63]. Conceptually, the ecosystem impact influenced by climate, soils, and vegetation because [66] and [68] for VCI is presented in Table 3.…”