基于北京二号与地理国情数据的林地提取

由于地理国情林地数据不包含实地面积小于400 m²的树木或四旁单排林，若仅利用地理国情的林地数据统计区域森林覆盖率，将对四旁树面积较大地区的林地统计结果产生较大误差。为提取区域内准确的林地覆盖与空间分布状况，本文借助地理国情地表覆盖数据，提出了一种基于北京二号高分辨率遥感影像的林地提取方法。首先，根据遥感影像光谱特征，将研究区按植被、道路、铁路、建筑用地进行地类划分，并基于遥感影像进行各地类的样本提取，通过可分离检验的样本利用最大似然分类提取研究区内植被覆盖范围；然后，借助地理国情地表覆盖数据，使用叠置分析剔除误分、错分地类，得到区域林地的空间分布。试验结果表明：(1)研究区内林地覆盖率为20.3%,尚未满足北京新一轮林地规划需求；(2)地理国情地表覆盖数据内林地面积占提取林地总面积的54.03%,说明在部分地区使用本文方法对地理国情林地数据进行补充是有必要的。通过将试验结果与遥感影像进行目视比对并结合外业调查结果发现，提取的林地空间分布情况与实际分布基本相符。本文为地理国情的应用提供了一种新方法，研究结果可辅助区域的绿色发展规划，有助于构建科学的生态空间格局。

Forest land extraction based on Beijing No.2 and geographical national conditions data

The forest land in the geographic national conditions data does not include trees or single-row forests with a field area of less than 400 m². If we only use the forest land data of geographical conditions to calculate the regional forest coverage rate, there will be a large error in the statistical results of the forest land in the area with large surrounding trees. For the above problems, in order to accurately extract the forest land cover and spatial extent in the region, a forest land extraction method based on the Beijing No.2 high-resolution remote sensing image is proposed in this paper by using the geographical and national land cover data. Firstly, according to the spectral characteristics of remote sensing images, the land types are divided according to vegetation, roads, railways and construction land, and the remote sensing images are used to extract samples of each type, and the maximum likelihood classification is used to extract the vegetation coverage for the samples that have passed the separable test. Then, with the help of the geographical and national land cover data, the overlay analysis was used to eliminate the misclassification and misclassification, and obtain the regional forest land coverage rate and spatial distribution. The results show that: ① The forest land coverage rate in the study area is 20.3%, which has not yet met the needs of a new round of forest land planning in Beijing. ② The forest land area in the geographic and national conditions data accounts for 54.03% of the total extracted forest land area, indicating that the use of this method in some areas is not enough. It is necessary to supplement the geographical conditions of forest land data. The experimental result is based on the visual comparison with remote sensing images combined with the field survey results, and it is believed that the spatial distribution of the extracted forest land is basically consistent with the actual distribution. The research provides a new method for the application of geographic and national conditions. The results can assist the regional green development planning and help to construct a scientific ecological spatial pattern.