Track 1-2-1: Assessment, Monitoring and Sustainability Indicators of Grassland Health
Description
Monitoring changes is critical information for rangeland management because vegetation is seasonally fluctuating green base protection of soil, therefore it is necessary to evaluate it at long-term period. In this study, abrupt and gradual trend changes were detected using BFAST and EVI-16 days of MODIS production. Time series results showed that 2000-2003 period was stable history and abrupt changes included 2003 onwards on monitoring history. The most negative trends were situated at center above of area with salty soil. Other parts of study area had positive and moderate trend. Our results suggest that BFAST is an automatic and repeatable method that can be used for a more accurate time of disturbance and breakpoints estimation. Using these, we can provide best grazing management for rangeland.
Rangelands are affected on fodder livestock, soil erosion and carbon cycle. So, it is needed to monitor and evaluate changes at the long term. In order to investigate ecological and driving forces on vegetation changes, time series would be best indicator. Detection of gradual and abrupt trend changes can be the first step understanding mechanism of factors affecting on vegetation (Waylen et al., 2014). Therefore it is critical to detect changes, understand change processes and their impact in terrestrial ecosystems. Satellite sensors provide consistent and repeatable measurements that enable capturing effects of many processes that cause change, including natural and anthropogenic disturbances (Forkel et al., 2013). BFAST integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting and characterizing abrupt trend changes within the trend and seasonal components (Verbesslet et al., 2013). BFAST monitor provides functionality to detect disturbance in near real-time and is flexible approach that handles missing data without interpolation. The objectives of our study were to: (1) demonstrate seasonally rainfall disturbances and (2) assess change dynamics on vegetation. To achieve these objectives, field samplings were conducted on rangeland of NE–Iran which is located between arid and humid zones.
Included in
BFAST: A Replacement of Climate Indicators for Monitoring Time-Series Using MODIS
Monitoring changes is critical information for rangeland management because vegetation is seasonally fluctuating green base protection of soil, therefore it is necessary to evaluate it at long-term period. In this study, abrupt and gradual trend changes were detected using BFAST and EVI-16 days of MODIS production. Time series results showed that 2000-2003 period was stable history and abrupt changes included 2003 onwards on monitoring history. The most negative trends were situated at center above of area with salty soil. Other parts of study area had positive and moderate trend. Our results suggest that BFAST is an automatic and repeatable method that can be used for a more accurate time of disturbance and breakpoints estimation. Using these, we can provide best grazing management for rangeland.
Rangelands are affected on fodder livestock, soil erosion and carbon cycle. So, it is needed to monitor and evaluate changes at the long term. In order to investigate ecological and driving forces on vegetation changes, time series would be best indicator. Detection of gradual and abrupt trend changes can be the first step understanding mechanism of factors affecting on vegetation (Waylen et al., 2014). Therefore it is critical to detect changes, understand change processes and their impact in terrestrial ecosystems. Satellite sensors provide consistent and repeatable measurements that enable capturing effects of many processes that cause change, including natural and anthropogenic disturbances (Forkel et al., 2013). BFAST integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting and characterizing abrupt trend changes within the trend and seasonal components (Verbesslet et al., 2013). BFAST monitor provides functionality to detect disturbance in near real-time and is flexible approach that handles missing data without interpolation. The objectives of our study were to: (1) demonstrate seasonally rainfall disturbances and (2) assess change dynamics on vegetation. To achieve these objectives, field samplings were conducted on rangeland of NE–Iran which is located between arid and humid zones.
