易湘生, 马尚杰, 游炯, 吴全, 何亚娟, 郭琳, 付野. 遥感调查中耕地解译面积精准核算[J]. 农业工程学报, 2016, 32(z1): 169-176. DOI: 10.11975/j.issn.1002-6819.2016.z1.024
    引用本文: 易湘生, 马尚杰, 游炯, 吴全, 何亚娟, 郭琳, 付野. 遥感调查中耕地解译面积精准核算[J]. 农业工程学报, 2016, 32(z1): 169-176. DOI: 10.11975/j.issn.1002-6819.2016.z1.024
    Yi Xiangsheng, Ma Shangjie, You Jiong, Wu Quan, He Yajuan, Guo Lin, Fu Ye. Accurate calculation of farmland area during remote sensing survey[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(z1): 169-176. DOI: 10.11975/j.issn.1002-6819.2016.z1.024
    Citation: Yi Xiangsheng, Ma Shangjie, You Jiong, Wu Quan, He Yajuan, Guo Lin, Fu Ye. Accurate calculation of farmland area during remote sensing survey[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(z1): 169-176. DOI: 10.11975/j.issn.1002-6819.2016.z1.024

    遥感调查中耕地解译面积精准核算

    Accurate calculation of farmland area during remote sensing survey

    • 摘要: 扣除小地物和线状地物是提高遥感调查中耕地解译面积精度的重要手段。该文选择安徽省濉溪县为研究区,以高分1号16 m多光谱影像作为数据源,在解译耕地面积的基础上,采用遥感解译与GIS空间运算相结合的方法对线状地物进行扣除,采用布设抽样样方的方法对小地物进行扣除,对研究区耕地解译面积进行精准核算。结果表明:1)濉溪县解译耕地面积为1 320.64 km2,广泛分布于全区,主要集中在中部和南部的四铺镇、百善镇、铁佛镇等地区,北部地区耕地分布相对较少;2)濉溪县共有45.14 km2的线状地物被解译为耕地,占整个研究区耕地解译面积的3.42%;3)濉溪县小地物平均扣除系数为3.51%,遥感解译耕地面积中有44.77 km2的小地物被解译为耕地;4)扣除线状地物和小地物后,濉溪县耕地面积为1 230.73 km2,全县解译耕地面积误差由6.57%降到0.68%,全部样方遥感解译平均误差的总体差异并不明显,单个样方在扣除小地物前后存在一定的差异。研究可为提高耕地解译面积精度提供思路与借鉴。

       

      Abstract: Abstract: Farmland is an important agricultural resource, which is directly related to the food security and is concerned by the public and government. As an important method, remote sensing images are usually interpreted to acquire the farmland area. However, for the reasons of spatial resolution of remote sensing images, many small features and linear features are interpreted into farmland, which surely affect the final farmland area. Thus, subtracting the small features and linear features is a key method to improve the accuracy of farmland area during the process of remote sensing survey. In this study, the Suixi County of Anhui province was selected as the study area. In addition, the GF-1 image with 16 meter resolution was used as data source. In order to get exact farmland area, different methods were used in various steps. Firstly, the farmland was interpreted by the fusion of image texture and spectral information according to the GF-1 image. Secondly, linear features were subtracted by remote sensing interpretation and spatial calculation of Geological Information System (GIS), and small features were subtracted according to the 36 sampling frames. Thirdly, farmland areas of interpretation in Suixi County were accurately calculated by subtracting the small features and linear features. Four important conclusions were got in this study, which were list as follows. (1) The total farmland area in the Suixi County was 1320.64km2 according to the results of interpretation. The farmland mainly distributed in the central regions (such as Sipu Town, Baishan Town) and southern regions (such as Shuangduiji Town, Nanping Town), while it relatively distributed small in the northern regions (such as Suixi Town, Liuqiao Town). (2) Liner features in the Suixi County mainly contains road, river and channel. There were 45.14km2 liner features which were interpreted into farmland according to the GF-1 image. The area of these liner features took up 3.42% of the total farmland area in the Suixi County. (3) According to the calculation of 36 sampling frames, the subtracting coefficients of small features were between 1.27% and 7.92%, and the mean of subtracting coefficient for the small features was 3.51% in the Suixi County. In addition to the linear features, there were still 44.77km2 small features which were interpreted into farmland. (4) Based on the results of interpretation, the finial farmland area in the Suixi County was 1230.73km2 after subtracting the small features and linear features. The absolute value of mean error for the farmland area was from 6.57% before subtracting the small features and linear features, while it was only 0.68% after the subtraction in the Suixi County. As for the 36 sampling frames, the absolute value of mean error was from 1.77% before the subtraction to 1.91% after the subtraction, which was not significant. The results in this study implicated many small features and linear features were interpreted into farmland. Subtracting the small features and linear features could obviously improve the accuracy of interpreted farmland area. This study could be helpful for improving accuracy of interpreted farmland area during the process of remote sensing survey.

       

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