插入参考文献，编译后出现如题错误There were undefined references.，输出的PDF里面也是? 我的参考文献bib代码是这样的，各种条目不管是用{}还是用""都是错误。我换着不同的编译器编译了多次依然如此，下面是bib代码，正文当中我插入的其它参考文献都是正常编译出来的，就下面这两篇文献不正常。 ``` @article{changexploring2013, title="Exploring spatiotemporal patterns of phosphorus concentrations in a coastal bay with {MODIS} images and machine learning models", volume="134", issn="0034-4257", url="http://www.sciencedirect.com/science/article/pii/S0034425713000746", doi="https://doi.org/10.1016/j.rse.2013.03.002", abstract="This paper explores the spatiotemporal patterns of total phosphorus (TP) in Tampa Bay (Bay), Florida, with the aid of Moderate Resolution Imaging Spectroradiometer (MODIS) images and genetic programming (GP) models. The study was designed to link TP concentrations with relevant water quality parameters and remote sensing reflectance bands in aquatic environments using in-situ data from a local database to support the calibration and validation of the GP model. The GP models show the effective capacity to demonstrate snapshots of spatiotemporal distributions of TP across the Bay, which helps to delineate the short-term seasonality effects and the decadal trends of TP in an environmentally sensitive coastal bay area. In the past decade, urban development and agricultural activities in the Bay area have substantially increased the use of fertilizers. Landfall hurricanes, including Frances and Jeanne in 2004 and Wilma in 2005, followed by continuous droughts from 2006 to 2008 in South Florida, made the Bay area an ideal place for a remote sensing impact assessment. A changing hydrological cycle, triggered by climate variations, exhibited unique regional patterns of varying TP waste loads into the Bay over different time scales ranging from seasons to years. With the aid of the derived GP model in this study, we were able to explore these multiple spatiotemporal distributions of TP concentrations in the Tampa Bay area aquatic environment and to elucidate these coupled dynamic impacts induced by both natural hazards and anthropogenic perturbations. This advancement enables us to identify the hot moments and hot spots of TP concentrations in the Tampa Bay region.", journal="Remote Sensing of Environment", author="Chang, Ni-Bin and Xuan, Zhemin and Yang, Y. Jeffrey", year="2013", keywords="Coastal bay, Genetic programming, MODIS, Nutrient monitoring, Remote sensing", pages="100-110", } @article{gaoremote2015, title = {Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques}, volume = {151}, issn = {0301-4797}, url = {http://www.sciencedirect.com/science/article/pii/S0301479714005775}, doi = {https://doi.org/10.1016/j.jenvman.2014.11.036}, abstract = {Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate statistical modeling techniques, demonstrated advantages for estimating the TP concentration in a large lake and had a strong potential for universal application for the TP concentration estimation in large lake waters worldwide.}, journal = {Journal of Environmental Management}, author = {Gao, Yongnian and Gao, Junfeng and Yin, Hongbin and Liu, Chuansheng and Xia, Ting and Wang, Jing and Huang, Qi}, year = {2015}, keywords = {Band combination, Lake Chaohu, Regional statistical modeling, Remote sensing, Total phosphorus}, pages = {33-43} } ```