期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII-B8
页码：945-950
出版社：Copernicus Publications
摘要：It is of great significance to obtain the crop condition information at early stages in the crop growing season. Sometimes it is even more important than acquiring the exact production after harvest time. Along with the development of remote sensing applications, satellite data has become the uppermost data source to monitor large-scale crop condition. In the last twenty years, more than a dozen of methods based on remote sensing data were developed to monitor crop condition in different countries and either the precision or the effectiveness of these crop condition monitoring methods has been improved greatly. Among these methods the mainly are: (1) Direct monitoring method with remote sensing indices, which monitor crop condition with indices such as NDVI or LAI according to its values. Usually the higher the indices are, the better the crop condition is. (2) Image classification method, which first did a supervised or unsupervised classification on the remote sensing data, then label each category as certain growth level with observed data of seedling's growing status which has spatial and temporal attributes. (3) Same-period comparing method, which could get the relative crop growing status for certain period by comparing the remote sensed data (NDVI, for example) of the period with the data of the period in the history (last year, mostly). In this method, difference and ratio are the indices mostly used. (4) Crop growth profile monitoring method, which is the contrast between year and year for crop growth profile and can reflect the crop growing continuance at time during crop growing season. Time series of NDVI during the crop season are used and crop growth profiles are formed by getting statistic of NDVI at certain scale such as a province. (5) Crop growing models method, this method use the crop growing model (also called crop growing modes) to simulate the growing status of crop and estimate the crop condition with the simulated result. These methods, along with their applications, are compared and analyzed and advantages and disadvantages of each method are supplied after comparing. As conclusion of the article, while the satellite data with high frequency and low spatial resolution is still the main data source, the method of crop condition monitoring with remote sensing data is developing in the following directions: (1) from qualitative monitoring to quantitative monitoring; (2) more and more indices such as LAI, TCI, VCI and NDWI are used to monitor crop condition in order to increase the monitoring precision; (3) some crop growing models which simulate the crop growing process are used to monitor crop condition; (4) GPS, GIS and RS data are combined to get a better monitoring result. The problems to be solved in crop condition monitoring models are also addressed
