Production of tree crown map using high resolution satellite imagery

在森林地区，很少有地标作为地面控制点（gcp）用于卫星图像或地图的配准。此外，在野外测量调查中，全球定位系统（GPS）提供的地理信息的精度不足以从卫星图像中识别单个树冠。在本研究中，我们提出了利用野外测量数据从卫星图像中识别单个Mae冠的方法。首先，为了获得现场测量数据，我们收集了测试场地单株树木的若干信息。这些是树木的立地、树干与最外层树枝在8个方向上的距离、胸高处的直径和树种。然后，利用野外测量数据，我们创建了包含单株树位置和形状的投影地面树冠图。树冠的每个形状都是八角形的。接下来，我们使用分水岭图像分割方法从IKONOS全色图像中检测树冠区域。利用光谱特征对分割区域进行分类，识别树冠。最后，从卫星影像中找出与野外实测数据相关的个别树冠。利用GPS设备的GCP，我们将卫星图像与投影的地面冠状图进行粗略配准。对于地图上的每个树冠，我们在卫星图像获得的分割区域中找到与地图上蜜蜂冠对应可能性最高的同一棵树。该算法利用图像和地图中树冠位置的适应度值和树冠的八角形形状进行树间匹配。在没有地面控制点的情况下，通过仿射变换获得适应度值最高的最优配准。因此，我们可以通过图像到地图的校正从卫星图像中识别单个树冠。

In forest area, there are few landmarks to be ground control points (GCPs) used for registration of satellite images or maps. Additionally, geographic information from the Global Positioning System (GPS) in field measurement survey is insufficient accuracy to identify individual tree crowns from satellite image. In this study, we propose the method of identifying individual Mae crowns from satellite image using field measured data. First, in order to obtain the field measured data, we collected several information of individual trees in the test site. These are the tree stand locations, the distances between the tree trunk and outermost branch in eight directions, the diameter at breast height, and tree species. Then, using the field measured data, we created the projected on-ground crown map which has the location and shape of individual trees. The each shape of tree crown is octagonal. Next, we detected the regions of tree crown from IKONOS panchromatic image using Watershed image segmentation method. The segmented regions were classified to discriminate tree crown using the feature of spectral signature. Finally, we found out individual tree crowns related with field measured data from satellite image. Using a GCP by GPS equipment, we performed roughly registration of the satellite image to the projaied on-ground crown map. For each tree crown in the map, we found out the same tree, which has the highest corresponding possibility to the bee crown in the map, among segmented regions obtained from satellite image. This tree-to-tree matching algorithm was performed using the fitness value of the location and octagonal shape of both tree crowns in image and map. We could obtain the optimum registration by affine transformation of highest fitness value without ground control points. Consequently, we could identify individual tree crowns from satellite image by image-to-map rectification.