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The enhancement of cultivated land quality is an important measure to improve the production capability and ensure the food safety. At the construction course of cultivated land quality informatization, novel methods and techniques are promising to improve the current working pattern as well as raise the efficiency of cultivated land quality management. Irrigation guarantee capability is an important element of cultivated land quality monitoring, evaluation and construction. Evapotranspiration (ET) derived from remote sensing can be used for rapid monitoring of irrigation guarantee capability of cultivated land at the regional scale. In order to improve the acquisition efficiency of the regional cultivated land quality monitoring, a new evaluation method was proposed for irrigation capability evaluation of cultivated land based on Moderate Resolution Imaging Spectroradiometer (MODIS) ET products. First, in order to reduce the representative errors of meteorological data, the relationship between the monthly potential evapotranspiration (PET) parameter derived from MODIS evaporation products and the reference crop evapotranspiration (ET0) calculated from observed meteorological data with the Penman-Monteith (P-M) formula was analyzed. The continuous ET0 in space was obtained from the regression model. And then, water requirements for crop were obtained by the map of crop type from the classification of Landsat TM data and space-continuous ET0. Furthermore, the annual water requirement was calculated according to the difference of the water requirement for crop and the rainfall which was effectively consumed by crop. Additionally, based on the regional water balance principle, the actual quantity of irrigation was obtained from the difference of actual evaporation derived from ET products of MODIS and effective rainfall. The evaluation index of irrigation guarantee capability is defined as the ratio of the annual irrigation requirement and the actual quantity of irrigation, and used for the monitoring and evaluation of cultivated land irrigation guarantee capability. Finally, application and analysis were conducted in Hengshui City, Hebei Province, China. The R2 of the regression model between the PET and ET0 from meteorological stations reached 0.89. And the calculated results of the evaluation index of irrigation guarantee capability from 2005 to 2012 accurately reflected temporal-spatial variations for the cultivated land irrigation capability. Meanwhile, the comprehensive evaluation of irrigation capability, which was from the supervised classification results based on actual survey, had a good agreement with the classification results of irrigation probability in the gradation on agriculture land quality which had been updated in 2012. The area with no grade difference was up to 37% of the total cells, 38% of the study area had one-grade difference, and the area with two-grade difference was 19% of the study area. The area with three-grade difference only accounted for 6%. The grade difference of more than 75% of the cultivated land was less than one grade. Errors were mainly concentrated in the cultivated land around the city, because the MOD16A2 product with 1-km resolution was inadequate to accurately represent the information of that complex planting structure of cultivated land, and this problem would be solved with the development and improvement of remote sensing earth observation systems with higher resolution. The evaluation index of irrigation capability proposed in this paper has the advantage of clear physical meaning and easy data accessing. The experiment results indicate that the method can meet the needs of the regional cultivated land quality monitoring and evaluation. [ABSTRACT FROM AUTHOR]

Identifying ecologically vulnerable areas and understanding the responses of phenology to negative changes in vegetation growth are important bases for ecological restoration. However, identifying ecologically vulnerable areas is difficult because it requires high spatial resolution and dense temporal resolution data over a long time period. In this study, a novel method is presented to identify ecologically vulnerable areas based on the normalized difference vegetation index (NDVI) time series from MOD09A1. Here, ecologically vulnerable areas are defined as those that experienced negative changes frequently and greatly in vegetation growth after the disturbances during 2000–2018. The number and magnitude of negative changes detected by the Breaks for Additive Season and Trend (BFAST) algorithm based on the NDVI time-series data were combined to identify ecologically vulnerable areas. TIMESAT was then used to extract the phenology metrics from an NDVI time series dataset to characterize the vegetation responses due to the abrupt negative changes detected by the BFAST algorithm. Focus was given to Jilin Province, a region of China known to be ecologically vulnerable because of frequent drought. The results showed that 13.52% of the study area, mostly in Jilin Province, is ecologically vulnerable. The vulnerability of trees is the lowest, while that of sparse vegetation is the highest. The response of phenology is such that the relative amount of vegetation biomass and length of the growing period were decreased by negative changes in growth for dense vegetation types. The present research results will be useful for the protection of environments being disturbed by regional ecological restoration. [ABSTRACT FROM AUTHOR]

The spatiotemporal change characteristics of Cultivated Land Productivity (CLP) are imperative for ensuring regional food security, especially given recent global warming, social development and population growth. Based on the hypothesis that the Gross Primary Productivity (GPP) is a proxy of land productivity, the Moderate Resolution Imaging Spectroradiometer (MODIS) data with 500-m spatial resolution and 8-day temporal resolution was employed by the Vegetation Photosynthesis Model (VPM) to calculate GPP in Jilin Province, China. We explored the level of CLP using the GPP mean from 2000 to 2018, and analyzed the changing trend and amplitude of CLP in the whole study period using both Theil–Sen median trend analysis and the Mann–Kendall (MK) test, and forecasted the sustainability of CLP with the Hurst exponent. The trend result and the Hurst exponent were integrated to acquire the future direction of change. The results revealed that: (1) The CLP level was generally high in the southeast and low in the northwest in cultivated land in Jilin, China. The area with the lowest productivity, located in the northwest of Jilin, accounted for 15.56%. (2) The majority (84.77%) of the area showed an increasing trend in 2000–2018, which was larger than the area that was decreasing, which accounted for 3.97%. (3) The overall change amplitude was dominated by a slightly increasing trend, which accounted for 51.48%. (4) The area with sustainability accounted for 33.45% and was mainly distributed in the northwest of Jilin. The area with anti-sustainability accounted for 26.78% and was mainly distributed in the northwest and central Jilin. (5) The Hurst exponent result showed that uncertain variation of CLP is likely to occur in the future over the entire region, and the central region is prone to display degeneration. Therefore, the results of this study indicated that quality improvement policy could be implemented for the middle-to-low yield fields in northwest Jilin, and dynamic monitoring and protection measures could be implemented for the areas with uncertain future changes and decreasing sustainability. [ABSTRACT FROM AUTHOR]