利用GIS地理统计模块预测海南岛植被指数季节性变化趋势

Prediction of the Seasonal Change Trend of NDVI in Hainan Island by GIS Geostatistical Analysis

虽然采用遥感图像提取的植被指数在空间上能较好的反映作物的状况,但其不能预测植被指数在空间上的变化范围,如果能从整体上了解不同市县在不同季节的平均植被指数值,就可以对该区域整体植被状态进行量化分析,也就可以从大范围内进行植被指数的预测分析。利用地理信息系统(G IS)和地统计学相结合的地理统计分析模块(ArcG IS Geostatistical Analyst),根据MOD IS遥感数据提取的每季度不同市县平均NDVI植被指数,采用Kriging插值的方法分析了海南岛归一化植被指数(NDVI)季节性变化趋势,并与实际采样值进行对比分析,结果表明,利用ArcG IS Geostatistical Analyst中的Kriging插值方法能较好地预测植被指数的空间分布范围。

Vegetation index information can be acquired from remote sensing images, but the spatial changing range of the index cant be predicted. If the average NDVI value of every city or county in different seasons can be known as a whole, it is possible for us to carry out quantitative analysis of the vegetation in every studied area and predict NDVI change trend. Hainan Island is situated in tropical monsoon area, where vegetation cover ratio is high. The MODIS remote sensing data are chosen to extract the average NDVI value for every city/county in Hainan Island because they are sensitive to the vegetation change in different seasons. ArcGIS Geostatistical Analysis combining GIS and Geostatistics is applied to analyze the seasonal NDVI change trend by Kriging method based on the MODIS data of NDVI in Hainan Island, and the outcome is compared with the measured NDVI from January to March. The result indicates that the Kriging method of ArcGIS Geostatistical Analysis is a good way to predict the change range of NDVI.