Selecting Appropriate Spatial Scale for Mapping Plastic-Mulched Farmland with Satellite Remote Sensing Imagery

Hasituya Hasituya,Jia Liu,Limin Wang,Zhongxin Chen

doi:10.3390/rs9030265

Abstract

In recent years, the area of plastic-mulched farmland (PMF) has undergone rapid growth and raised remarkable environmental problems. Therefore, mapping the PMF plays a crucial role in agricultural production, environmental protection and resource management. However, appropriate data selection criteria are currently lacking. Thus, this study was carried out in two main plastic-mulching practice regions, Jizhou and Guyuan, to look for an appropriate spatial scale for mapping PMF with remote sensing. The average local variance (ALV) function was used to obtain the appropriate spatial scale for mapping PMF based on the GaoFen-1 (GF-1) satellite imagery. Afterwards, in order to validate the effectiveness of the selected method and to interpret the relationship between the appropriate spatial scale derived from the ALV and the spatial scale with the highest classification accuracy, we classified the imagery with varying spatial resolution by the Support Vector Machine (SVM) algorithm using the spectral features, textural features and the combined spectral and textural features respectively. The results indicated that the appropriate spatial scales from the ALV lie between 8 m and 20 m for mapping the PMF both in Jizhou and Guyuan. However, there is a proportional relation: the spatial scale with the highest classification accuracy is at the 1/2 location of the appropriate spatial scale generated from the ALV in Jizhou and at the 2/3 location of the appropriate spatial scale generated from the ALV in Guyuan. Therefore, the ALV method for quantitatively selecting the appropriate spatial scale for mapping PMF with remote sensing imagery has theoretical and practical significance.

Highlights

The plastic mulching technique has been applied extensively both in China and in the rest of the world, due to its positive effects of improving hydrothermal conditions in farmland, promoting crop growth, expanding planting area and increasing crop yield
We found that (1) there was relatively less attention paid to mapping the plastic-mulched farmland (PMF); (2) the remote sensing data for mapping PMF were medium or coarse spatial resolution imagery, the high-spatial-resolution imagery has not been used until now; (3) there were no studies with an emphasis on the selection of the appropriate spatial scale for remote mapping of PMF
We found that the appropriate spatial scales generated from the average local variance (ALV) were at a range of 8 m–20 m, and the highest classification accuracy from a Support Vector Machine (SVM) was at the spatial resolution of 6 m and 8 m in Jizhou and at the 6 m and 12 m in Guyuan (Table 4)

Summary

Introduction

The plastic mulching technique has been applied extensively both in China and in the rest of the world, due to its positive effects of improving hydrothermal conditions in farmland, promoting crop growth, expanding planting area and increasing crop yield. Plastic film is widely used for covering greenhouses, medium or low tunnels and for mulching. China has the largest area of plastic-mulched farmland (PMF) in the world, and that area has been growing more and more rapidly. The 0.12 million ha area mulched by plastic film in 1981 increased to 19.79 million ha in 2011 [1] and to 25 million ha in. From the view of the short-term agricultural production, the practices of plastic mulching bring many benefits to farmers by avoiding unfavorable growing conditions. Due to the special properties of plastic film itself and its expansive and unreasonable use, a set of environmental

Methods

Results

Discussion

Conclusion