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利用Landsat系列数据集进行1984-2023EVI指数趋势分析其主要目的是进行长时序的分析，这里我们选用EVI指数，然后进行了4个月的分析，查看其最后的线性趋势以及分布状况。
EVI指数：
EVI指数（Enhanced Vegetation Index，增强型植被指数）是一种反映植被生长状态的遥…简介：
利用Landsat系列数据集进行1984-2023EVI指数趋势分析其主要目的是进行长时序的分析，这里我们选用EVI指数，然后进行了4个月的分析，查看其最后的线性趋势以及分布状况。
EVI指数：
EVI指数（Enhanced Vegetation Index，增强型植被指数）是一种反映植被生长状态的遥感指数，它结合了植被指数的红光波段和近红外波段的信息，可以消除植被覆盖度、土壤背景和大气影响等因素对遥感数据的影响，用于研究植被生长和陆地生态系统的动态变化。EVI指数的计算公式为：EVI=(2.5*(NIR-Red))/(NIR+6*Red-7.5*Blue+1)，其中NIR、Red和Blue分别为近红外、红光和蓝光波段反射率。EVI指数的取值范围在-1到1之间，数值越大表示植被覆盖度越高，反之则越低。
函数：
ee.Filter.calendarRange(start,end,field)这个用来筛选指定年月日特定时间的函数
Returns a filter that passes if the object's timestamp falls within the given range of a calendar field. Themonth,day_of_year,day_of_month, andday_of_weekare 1-based. Times are assumed to be in UTC. Weeks are assumed to begin on Monday as day 1. Ifendstartthen this tests forvalue=startORvalue=end, to allow for wrapping.
Arguments:
start(Integer):
The start of the desired calendar field, inclusive.
end(Integer, default: null):
The end of the desired calendar field, inclusive. Defaults to the same value as start.
field(String, default: "day_of_year"):
The calendar field to filter over. Options are:year,month,hour,minute,day_of_year,day_of_month, andday_of_week.
Returns:Filter
ee.ImageCollection.fromImages(images)从列表中讲影像转化为影像集合
Returns the image collection containing the given images.
Arguments:
images(List):
The images to include in the collection.
Returns:ImageCollection ee.Algorithms.If(condition,trueCase,falseCase)这个是防止数据集中出现没有影像的情况，然后进行条件筛选
Selects one of its inputs based on a condition, similar to an if-then-else construct.
Arguments:
condition(Object, default: null):
The condition that determines which result is returned. If this is not a boolean, it is interpreted as a boolean by the following rules: Numbers that are equal to 0 or a NaN are false. Empty strings, lists and dictionaries are false. Null is false. Everything else is true. trueCase(Object, default: null):
The result to return if the condition is true.
falseCase(Object, default: null):
The result to return if the condition is false.
Returns:Object
ui.Chart.feature.groups(features,xProperty,yProperty,seriesProperty)按照矢量组加载时序图表
Generates a Chart from a set of features. Plots the value of a given property across groups of features. Features with the same value of groupProperty will be grouped and plotted as a single series. X-axis = xProperty values. Y-axis = yProperty values. Series = Feature groups, by seriesProperty. Returns a chart.
Arguments:
features(Feature|FeatureCollection|ListFeature):
The features to include in the chart.
xProperty(String):
Property to be used as the label for each feature on the x-axis.
yProperty(String):
Property to be plotted on the y-axis.
seriesProperty(String):
Property used to determine feature groups. Features with the same value of groupProperty will be plotted as a single series on the chart.
Returns:ui.Chart
代码：
var counties = ee.FeatureCollection("TIGER/2018/Counties"),elev = ee.Image("USGS/NED"),wdpa = ee.FeatureCollection("WCMC/WDPA/current/polygons"),slr_high = ee.FeatureCollection("users/caitlittlef/Acadia_SLR"),marsh = ee.FeatureCollection("users/caitlittlef/Acadia_marsh"),l8 = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2"),l5 = ee.ImageCollection("LANDSAT/LT05/C02/T1_L2"),margin = ee.FeatureCollection("users/caitlittlef/Acadia_marsh_slr_margin"),slr_buff = ee.FeatureCollection("users/caitlittlef/Acadia_SLR_buffer"),marsh_buff = ee.FeatureCollection("users/caitlittlef/Acadia_marsh_buffer"),bass_harbor = /* color: #90d614 */ee.Geometry.Point([-68.34446051531992, 44.257472150621076]),thompson_island = /* color: #90d614 */ee.Geometry.Point([-68.36250246923403, 44.4225955588721]),babson_creek = /* color: #90d614 */ee.Geometry.Point([-68.32728158629772, 44.37497962957902]),sch
