Crop growth monitoring with remote sensing attempt to provide real-time information of crop growth state to guide filed management during crop growth period and early yield estimation. Many researches of how to use remote sensing to monitor crop growth state have been done in the last couple of years, although most of them completed their study on the regional scale rather than on field scale. But more accurate crop growth state information on field scale is really needed for us when we want to apply the monitoring result to guide the use of pesticides and fertilizers, establish more accurate yield estimation models. Therefore, we propose monitoring crop growth state on field scale using Planet scope (PL) imagery in the paper. Firstly, we chose an image of the first half of July to detect the edge of field for it is not covered by crops at this time, a new feature was computed based on original PL image to enhance the comparison between field edge and field itself. Then canny algorithm and morphological operations were used to detect and modified field edge, respectively. Secondly, the edge data was used to complete image segmentation to get field data. Finally, we use our method to evaluate the crop growth state of each filed and compare it with traditional methods. Our experiments result demonstrates that: 1) PL image is capable of detecting field edge in north area of China, the area of the largest field we detect is about 850000㎡（8.5 Ha）and the smallest is about 2250㎡ (0.225 Ha)；2) crop growth monitoring on field scale is more accurate than on regional scale, the variance of RS monitoring index can indicate internal crop growth state of each field, and the monitoring result can truly guide field management; 3) with the excellent repeat observation ability of PL satellite, we can depict the crop growth process in detail on field scale, which is useful to obtain more accurate yield prediction.