Assessing agricultural drought at a regional scale using LULC classification, SPI, and vegetation indices: case study in a rainfed agro-ecosystem in Central Mexico

Abstract

Satellite observations of the spectral properties of vegetation can provide insights on crop conditions and yield, and, furthermore, can monitor the impact of droughts. In the case of rainfed crops grown for self-sufficiency, a drought can result in significant human suffering, highlighting the need to understand how droughts affect the landscape in such regions. This paper uses remote sensing to assess the phenomenological impacts of two isolated droughts, distinguishing the response of different vegetation covers in semiarid developing regions where rainfed agriculture is common. Using the standardized precipitation index, one normal and two dry years were selected (2000, 2005, and 2011, respectively). An original protocol for land use land cover (LULC) classification that combines climatic, topographic, and reflectance information from 18 Landsat ETMC images was applied to subsequently distinguish drought effects in different classes through the selected years. Finally, two vegetation indices (normalized difference vegetation index (NDVI) and vegetation condition index (VCI)) were calculated to detect drought severity impacts over the different LULC classes. This approach was tested in Central Mexico and provided accurate information on the location and extent of areas affected by drought. The proposed approach can be used as a system for drought risk management in semi-arid developing regions.

High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico

“…In a previous study by SIERRA-SOLER et al [2015] performed for the same study area as the present paper, a precipitation analysis using the Standardized Precipitation Index of monthly precipitation from January 1980 to December 2012 was performed. In this study the SPI was processed using this monthly data.…”

“…Droughts occur in all climatic zones and are mostly related to the reduction of precipitation received over an extended period, such as a season or a year [MAHMOOD et al 2015;SAADAT et al 2011;SIERRA-SOLER et al 2015]. The impacts of a drought increase slowly and often accumulate over many months, and may linger years after the end of the drought [BELAYNEH et al 2014;SAADAT et al 2014].…”

“…This season in central Mexico corresponds to June and August, and the years analyzed in this study were 2000 and 2005. These specific years were chosen based on a previous study for the same study area by SIERRA-SOLER et al [2015] that analyzed Standardized Precipitation Index SPI trends for the period 1975-2013. In this study, the year 2000 consistently showed positive values of SPI (normally wet conditions) and 2005 continually showed negative SPI values (corresponding to abnormally dry conditions).…”

Assessment of spatio-temporal vegetation dynamics in tropical arid ecosystem of India using MODIS time-series vegetation indices

“…Vegetation plays a pivotal role in the global atmospheric, terrestrial ecosystem, hydrologic, carbon cycles, climate change, and drought monitoring (Peng et al 2012;De Keersmaecker et al 2014;Sierra-Soler et al 2015;Winkler et al 2017;Measho et al 2019). Changes occurred in vegetation constitute as good indicators in ecological and environmental assessment from local to global scales (Sobrino and Julien 2011;Schucknecht et al 2013;Guay et al 2014).…”

Risk of Low Productivity is Dependent on Farm Characteristics: How to Turn Poor Performance into an Advantage

“…Hence, comprehensive data on production capacity are needed with good spatial and temporal coverage. Open satellite data haves opened many new solutions for agriculture and many of them support the large-scale transformation of agriculture: e.g., in the estimation of yields [19][20][21] as well as the identification of crops [16], crop conditions [22,23], pre-crop values for crop sequence [24] and providing sets of sustainable intensification indicators [25].…”