CAJ | 학술논문

线状地物又称为线性地物，是一种普遍存在的土地利用方式。在遥感图像上，线状地物大量存在，这种存在表现为线状地物的可见性，即线状地物的图像特征表现为数个像元宽度的狭长型地物；另一方面，大量线状地物被“淹没”在遥感图像的混合像元中，这部分线状地物在遥感图像上具有相对不可见性。在面状地物解译中，线状地物常常由于遥感影像分辨率有限而包含在面状地物中，使面状地物解译结果偏大而不够准确。因此，准确解译线状地物可以校正面状地物解译结果。Landsat TM8影像与GF-1影像作为近几年新出现的高质量高分辨率卫星遥感影像，在各行各业中应用较为广泛，在农业遥感中亦是如此。在农作物面积估算中，Landsat TM8影像与GF-1影像线状地物扣除技术的精确程度直接影响农作物面积估算精度。Landsat TM8影像与GF-1影像线状地物实际宽度与解译宽度对比研究对于农作物面积估算和估产具有重大意义。由于分辨率相差较大，在线状地物解译中，GF-1影像具有明显优势。该文以23景 Landsat TM8影像和14景GF-1影像为基础，运用统计学方法对黑龙江省341条线状地物实际宽度与解译宽度做对比研究。结果表明，对线状地物解译精度影响较大的主要因素为卫星遥感影像分辨率。Landsat TM8影像解译精度较差（|夸张系数|>50%）的线状地物共94条，占全部线状地物的27.5660%；在这部分线状地物中，通常是解译宽度远大于实际宽度；以线状地物实际宽度分类中的0～10 m 类别中，线状地物的解译精度最差，而按走向分类和按类型分类对线状地物解译精度影像不大。GF-1影像解译精度较差的线状地物共有29条，占全部线状地物的8.5044%，在这部分线状地物中，通常是解译宽度远大于实际宽度。
선상지물우칭위선성지물，시일충보편존재적토지이용방식。재요감도상상，선상지물대량존재，저충존재표현위선상지물적가견성，즉선상지물적도상특정표현위수개상원관도적협장형지물；령일방면，대량선상지물피“엄몰”재요감도상적혼합상원중，저부분선상지물재요감도상상구유상대불가견성。재면상지물해역중，선상지물상상유우요감영상분변솔유한이포함재면상지물중，사면상지물해역결과편대이불구준학。인차，준학해역선상지물가이교정면상지물해역결과。Landsat TM8영상여GF-1영상작위근궤년신출현적고질량고분변솔위성요감영상，재각행각업중응용교위엄범，재농업요감중역시여차。재농작물면적고산중，Landsat TM8영상여GF-1영상선상지물구제기술적정학정도직접영향농작물면적고산정도。Landsat TM8영상여GF-1영상선상지물실제관도여해역관도대비연구대우농작물면적고산화고산구유중대의의。유우분변솔상차교대，재선상지물해역중，GF-1영상구유명현우세。해문이23경 Landsat TM8영상화14경GF-1영상위기출，운용통계학방법대흑룡강성341조선상지물실제관도여해역관도주대비연구。결과표명，대선상지물해역정도영향교대적주요인소위위성요감영상분변솔。Landsat TM8영상해역정도교차（|과장계수|>50%）적선상지물공94조，점전부선상지물적27.5660%；재저부분선상지물중，통상시해역관도원대우실제관도；이선상지물실제관도분류중적0～10 m 유별중，선상지물적해역정도최차，이안주향분류화안류형분류대선상지물해역정도영상불대。GF-1영상해역정도교차적선상지물공유29조，점전부선상지물적8.5044%，재저부분선상지물중，통상시해역관도원대우실제관도。
Linear feature general exist in the nature and RS images as a type of land use. Linear feature's image feature is long and narrow object on the RS images, and it is visibility to the human eyes. On the other hand , a large number of linear feature hide in the mixed pixel in the RS images for their relative invisibility. In the surface feature interpretation, linear feature always includes to the surface feature to enlarge the achievement for the limited resolution. So, accurate linear feature interpretation can supply the surface feature result from deduction technology. Landsat TM8 image and GF-1 image have been extensively applied in different trade for their high quality and high resolution in several years, so as to agricultural RS field. In the crop area estimation, the accuracy of linear features extraction in Landsat TM8 image and GF-1 image can impact on the crop area estimation accuracy directly. So, the study of linear feature real width and interpretation width has a great significance for the crop area and yield estimation. GF-1 image has obvious advantage in linear feature interpretation for the higher resolution. Research areas were selected in Heilongjiang province, involving 56 counties and cities. The field investigation time was Sep 22-28, 2013, and 341 linear features were einvestigated. The a certain number of linear features in field investigation was selected in random, then recorded the width with the tape, at the same time ,use the Trimbes GPS positioning. Preliminary statistics the result of the Heilongjiang Province linear feature field investigation in 2013, then classification the linear feature with trend, type, real width. There are 3 catalogs and 13 type, including south-north trend, east-west trend, northeast-southwest trend, northwest-southeast trend, highway, field road, forest belt, ditch, 0-10 m, 10-20 m, 20-30 m, 30-40 m, >40 m and so on. 23 Landsat TM8 images and 14 GF-1 images were selected for the linear feature interpretation, imaging time concentrated in Jul 11,2013-Sep 18,2013. The primary compression package of the Landsat TM8 image's the fifth band TIFF file, the sixth band TIFF file, the forth band TIFF file were selected for layer stack, and then resampling the layer stack result to Albers conical projection, Krasovsky ellipsoid, Pulkovo 1942 coordinate system file. The .img file's named way is<satellite name and number>_<orbit number>_<imaging time>_<projection>.img. The .img file's band combination is R:1, G:2, B:3. The primary compression package of the GF-1 image's TIFF image was handled to receive the .img file with Albers conical projection, Krasovsky ellipsoid, Pulkovo 1942 coordinate system file. The .img file’s named way is < satellite name and number >_<sensor>_<center point longitude>_< center point latitude>_< imaging time >_<projection>.img. The .img file's band combination is R:4, G:3, B:2. The study compared the 341 linear features’ real width and interpretation width though statistics method in Heilongjiang province using 23 Landsat TM8 images and 14 GF-1 images. The results showed that all the trends linear feature's real width and interpretation width had a large standard deviation, and coefficient of variation of GF-1 images interpretation width’s standard deviation and coefficient of variation were smaller than the Landsat TM8 images interpretation width's. According to the classification of linear feature type, highway and ditch’s standard deviation and coefficient of variation had a vary widely to the field way and forest belt's, and GF-1 images interpretation width's standard deviation and coefficient of variation were smaller than the Landsat TM8 images interpretation width's. According to the classification of real width, because all the sample values are in the same interval, all the types had a small standard deviation and coefficient of variation except real width>40m, and GF-1 images interpretation width's standard deviation and coefficient of variation were smaller than the Landsat TM8 images interpretation width's. It means that RS satellite image's resolution determined the linear feature interpretation precision. 94 linear features had low interpretation precision with Landsat TM8 images interpretation (the absolute value of the exaggeration more than 50%), for 27.5660%of the entire linear feature, and in this part, interpretation width always larger than real width, and the category of 0-10 m had a worst interpretation precision, the category of trend and type had no influence to the linear feature interpretation accuracy. 29 linear features had low interpretation precision with GF-1 images interpretation, for 8.5044%of the entire linear feature, and in this part, interpretation width always much greater than real width.