Land Productivity Evaluation Based On 3S Technolog

As the carrier of food security,Arable land is the basis for the growth of crops and a matter of human survival and development.To ensure national food security,the most fundamental thing is to protect the arable land.Accurate and timely agricultural condition determination is required for regional crop yield estimation,agricultural cultivation structure optimization,and other related tasks.There is great potential for expansion in the application of remote sensing technology to gather data on agricultural planting structure.Soil organic matter,one of the fundamental elements of soil,acts as a critical indicator of arable soil productivity,condition,and deterioration.Due to the influence of complex factors and human factors in soil formation process,soil organic matter of arable land has large spatial and temporal variability,and it is especially important to monitor the soil nutrient distribution status by grasping the spatial distribution information of soil organic matter content on a large scale in real time.Crop planting structure monitoring,yield estimation and soil organic matter estimation are important areas of precision agricultural remote sensing,and this research is of great significance to the scientific guidance of crop planting structure and the formulation of agricultural policies.In this paper,Hailun,a typical black soil area in Heilongjiang Province,is selected as the study area,and the crop planting structure in the study area is extracted based on the high-resolution remote sensing image data source.Taking maize,the main grain crop,as an example,the CASA model method is used to estimate the regional maize yield level,and the related soil organic matter inversion model is established by using the spectral reflectance and soil organic matter content of the corresponding sample points,combining the spatial distribution information of soil organic matter,slope,soil degradation index,vegetation index and maize yield estimation results to establish an evaluation system to evaluate the land productivity of maize growing areas in the study area and to study the feasibility of remote sensing technology in yield estimation in black soil areas.(1)The data source for this study included Sentinel-2A remote sensing pictures with a 10 m resolution.The crucial period of crop identification and its distinctive parameters are established using weather data and spectral features,and then the object-oriented decision tree classification model is built.The spatial distribution of maize cultivation in the study area in 2021 was obtained by constructing an object-oriented decision tree classification model.The results showed that the features showed a high degree of consistency in spatial distribution.The remote sensing interpretation improves the efficiency while ensuring the classification accuracy of crop planting structure extraction;(2)Based on the CASA model based on light energy utilization,the annual accumulation of regional net primary production capacity in Hailun in 2021 was predicted to build the maize yield estimating model,using software like ArcGIS and ENVI.The results showed that the maize yield estimated by the model in the study area was relatively close to the actual maize yield in 2021,and its estimated yield results had a strong reference value;(3)The sensitive wavebands were examined in SPSS software on the distribution of soil organic matter and data from remote sensing images in 2012.An inversion model of soil organic matter was created using spectrum reflectance as the independent variable and soil organic matter content as the dependent variable.It was possible to gather information on the spatial distribution of soil organic matter in 2021.The results showed that there was a strong correlation between maize yield and soil organic matter when the results of maize yield estimation and soil organic matter inversion in the study area were correlated;(4)With developing thorough assessment indices based on slope,soil degradation level,soil organic matter,vegetation index,and maize yield level,the land productivity evaluation system was constructed.To achieve complete evaluation of land productivity,a model for comprehensive evaluation of land productivity was established.The results show that the application results of the method are basically consistent with the spatial pattern of farmland cultivation area and grain yield,indicating that the method is a good guide for farmland cultivation area and grain yield.