基于MODIS数据的新疆草地物候提取方法及变化趋势分析

Grassland phenology extraction for Xinjiang Province and trend analysis using MODIS data

基于遥感手段监测植被物候涉及两个重要步骤,一是植被指数的重构方法,二是植被物候参数提取方法的选择。不同区域植被物候重构与提取方法的优劣尚无定论,有必要开展不同方法之间的对比分析,从而找到适合某区域最优的遥感提取方法。本研究基于非对称性高斯函数拟合法(asymmetric gaussian,A-G)、双逻辑斯蒂函数拟合法(double logistic,D-L)、Savitzky-Golay滤波法(S-G)和土地覆盖动态产品(MCD12Q2)4种方法反演了2001-2019年新疆地区草地的返青期(start of growing season,SOS),通过4种方法提取结果对比,找到了适合提取新疆地区返青期的最优模型,并以此对新疆草地返青期时空变化进行研究。结果表明:1)A-G方法反演的新疆草地返青期的结果最佳。A-G和实测点的返青期相关性(R=0.879)较高,均方根误差较小(RMSE=16.395 d)。空间上,A-G方法提取的返青期标准差(<30 d)的面积比例最多,达到82.19%。2)近19年,新疆草地返青期主要集中在第60~140天,且具有自北向南逐渐推迟的明显地域差异。北部准噶尔盆地和伊犁河谷区域的草地返青时间最早,早于第80天,而阿尔泰山、天山中部及昆仑山等区域的草地返青时间最晚,晚于第140天。不同草地类型返青期存在明显的差异,高寒草甸与高寒草原的返青时间最晚,而温性荒漠返青时间最早。3)2001-2019年新疆草地返青期总体呈现微弱的推迟趋势,推迟的面积比例约为53.07%。其中,低地草甸、温性荒漠和高寒荒漠的返青期呈现推迟的变化趋势,而温性草原、高寒草原及高寒草甸的返青期表现为提前趋势。

There are two important steps when monitoring vegetation phenology by remote sensing.The first is separation of‘vegetation data’from‘noise’such as cloud cover in the MODIS satellite data so as to obtain the best possible estimate or“reconstruction”of the normalized difference vegetation index(NDVI)and its changes over the time period of interest.The second is the extraction of estimates of vegetation phenology parameters from the reconstructed NDVI data.The comparative merits or demerits of different available NVDI reconstruction and vegetation phenology extraction methods and their suitability in different regions are still little-studied.It is necessary to carry out a comparative analysis of different methods and to compare results with field data to identify the optimal remote sensing extraction methodology for a particular region.Here we report a comparison of four extraction methods to extract the start of season(SOS)date for grassland in Xinjiang from 2001 to 2019.The four methods compared were:the asymmetric Gaussian function fitting method(asymmetric gaussian,A-G),the double logistic function fitting method(double logistic,D-L),Savitzky-Golay filter method(S-G)and the land cover dynamic product(MCD12Q2).Through comparison of the extraction results obtained by the four methods,the optimal model for extracting SOS was found,and the regional variation and change over the 19-year study period in the SOS in Xinjiang Province were evaluated.The main conclusions were as follows:1)The A-G extraction method provided the best estimate of the SOS for Xinjiang grassland.The correlation(R=0.879)between A-G estimates of SOS and the SOS recorded at field-measured points was higher and the root mean square error(RMSE=16.395 d)was smaller.Spatially,the standard deviation for SOS measured by the A-G method was less than 30 d for 82.19%of the area evaluated,compared with 76.53%and 67.98%for D-L and S-G methods,respectively.The MCD12Q2 method had a smaller standard error but there were large areas of terrain where no estimate of SOS could be provided.2)Over the 19 years for which data were evaluated,the SOS in Xinjiang occurred as early as the 60th and as late as the 140th day of the year,with obvious regional differences,SOS being earlier in the north and later in the south.In the north of Junggar Basin and Ili river valley,the SOS was earlier than the 80th day,while in the Altai Mountain,central Tianshan Mountain and Kunlun Mountain the SOS was later than the 140th day.The SOS of different grassland types had obvious differences.For example,SOS of alpine meadow and alpine grassland was the latest,while SOS of temperate deserts was the earliest.3)From 2001 to 2019,SOS in Xinjiang showed interannual variation of approximately 15 days between early and late years,with a trend over time to later SOS in lowland meadow,temperate desert and alpine desert,and earlier SOS in temperate grassland,alpine grassland and alpine meadow.