Land Evaluation In Semi-arid Region Using Remotely Sensed Derived Vegetation Index Under Extreme Drought Event

Land evaluation is an important prerequisite for scientific and rational use of land resources and also a basis of land management.Factors affecting land productivity were currently evaluated to classify land productivity according to the evaluation criteria derived from their characteristics.However,the effects of various factors on crop growth are different,and relationships between factors are not very clear.Therefore,previous land evaluation results were not accurate enough.In addition,the current land evaluation with many influencing factors under a huge workload survey is very difficult to apply.Different regions have different natural conditions,so key factors affecting and restricting the land production capacity are also different.In the semi-arid region,conditions including illumination,heat,and soils are generally good,whereas water mainly restrict the land productivity.The growth status of crops is the result of adaptation to land productivity,and is a comprehensive reflection and the most direct performance of the land characteristics.Under extreme drought conditions,crop growth in semi-arid areas also showed extreme state due to the lack of water supply,which indicates regional land productivity.Remote sensing technique has characteristics including quick,accuracy,periodic observation,and large coverage.It has become an effective method to monitor crop growth conditions.Remote sensing vegetation index is the best indicator of vegetation growth,and is widely used in the evaluation of plant biomass.An example of Chaoyang in semi-arid area is studied.The vegetation index of crop growth status in extreme drought conditions,from remote sensing images with high temporal resolution,was used to classify land productivity based on crop growth difference.Analysis of the vegetation index and its change rate on data of several continuous years(2001-2015),typical years(2008-2010),and extreme drought year 2009 were conducted to address results of crop growth and its spatial distribution in Chaoyang area.Comparisons of evaluation results between using the vegetation index based on land evaluation(VIBLE),agricultural land classification and gradation,and arable land productivity evaluation were done following a field survey to address the accuracy and validity of VIBLE.Finally,a quick,accurate,and efficient land evaluation method for land evaluation is explored and proposed.Some meaningful results were listed as follows:(1)Previous data of Chaoyang was analyzed.The results showed that Chaoyang is located in the warm temperate semi-arid region.Natural factors of illumination,heat,and soils are generally optimal,whereas water mainly restricts the land productivity.The average annual precipitation is only about 500 mm.The spatial and temporal distribution of precipitation is very uneven,which is one of main causes for frequent drought in the region.In addition,spring and autumn wind is more prone to cause drought.Therefore,water is the main restricting factor for land productivity.(2)The comparison between land evaluation results of VIBLE and observational points was conducted.The land evaluation accuracy of extreme drought year 2009 data and several continuous years(2001-2015),was higher than that using typical years(2008-2010)data.The accuracy of VIBLE land evaluation results was higher than that using agricultural land classification and gradation and arable land fertility evaluation.The method using normalized difference index(NDVI)of extreme drought year 2009 data to classify land was finally demonstrated to be simple and effective.(3)According to the difference of NDVI under extreme drought,the productive capacity of arable land in the study area was evaluated.Four levels of evaluation results were divided(e.g.suitability level for planting corn)using average values and standard deviation as intervals,and the grid land evaluation map was finally obtained.The land evaluation method based on vegetation index extracting from remote sensing data thus was proposed.(4)General processes of VIBLE were proposed and listed as follows.Extreme drought period according to climatic data was firstly identified;crop growth key period(autumn for the northern corn)was selected;available remote sensing images were determined(high temporal resolution MODIS images are available,but with low spatial resolution;high spatial resolution images may not be available at critical times);the vegetation remote sensing vegetation index was extracted to classify the crop growth;finally,land productivity in the study area was classified.The land evaluation method used in this study is simple,time-saving,fast,and accurate.The results(the productivity of land and its spatial distribution)are expressed in the form of grid,which can objectively reflect the spatial variability of land quality,and has a realistic guiding significance for land use planning and land management.This research will provide a valuable reference for land evaluation in other areas.