Google Earth Engine ——Landsat 5 TM合成影像8天/32天/年际归一化植被指数（NDVI）指数数据集

These Landsat 4 TM composites are made from Level L1T orthorectified scenes, using the computed top-of-atmosphere (TOA) reflectance. See Chander et al. (2009) for details on the TOA computation.

As of May 1, 2017, the USGS is no longer producing Pre-Collection Landsat, and therefore this collection is complete. Please switch to a Collection 1-based dataset. See this documentation page for more information.

The Normalized Difference Vegetation Index is generated from the Near-IR and Red bands of each scene as (NIR - Red) / (NIR + Red), and ranges in value from -1.0 to 1.0.

These composites are created from all the scenes in each annual period beginning from the first day of the year and continuing to the last day of the year. All the images from each year are included in the composite, with the most recent pixel as the composite value.

这些Landsat 4 TM合成物是由L1T级正射场景制作的，使用计算的大气层顶部（TOA）反射率。关于TOA计算的细节，见Chander等人（2009）。

从2017年5月1日起，美国地质调查局不再生产预收集的Landsat，因此这个收集已经完成。请切换到基于集合1的数据集。更多信息请参见本文档页面。

归一化植被指数由每个场景的近红外和红色波段生成，为（近红外-红色）/（近红外+红色），数值范围为-1.0至1.0。

这些合成物是由每个年度的所有场景创建的，从该年的第一天开始，一直到该年的最后一天。每一年的所有图像都包括在合成中，以最近的像素作为合成值。

Dataset Availability

- 1994-01-01T00:00:00

Dataset Provider

USGS

Collection Snippet

ee.ImageCollection("LANDSAT/LT4_L1T_ANNUAL_NDVI")

Bands Table

* = Values are estimated

使用说明：

Landsat datasets are federally created data and therefore reside in the public domain and may be used, transferred, or reproduced without copyright restriction.

Acknowledgement or credit of the USGS as data source should be provided by including a line of text citation such as the example shown below.

(Product, Image, Photograph, or Dataset Name) courtesy of the U.S. Geological Survey

Example: Landsat-7 image courtesy of the U.S. Geological Survey

See the USGS Visual Identity System Guidance for further details on proper citation and acknowledgement of USGS products.

Landsat数据集是联邦创建的数据，因此属于公共领域，可以在没有版权限制的情况下使用、转让或复制。

对美国地质调查局作为数据来源的确认或信用，应通过包括一行文字引用来提供，如下面的例子。

(产品、图像、照片或数据集名称）由美国地质调查局提供。

例子。Landsat-7图像由美国地质调查局提供

请参阅美国地质调查局视觉识别系统指南，了解有关美国地质调查局产品的正确引用和鸣谢的进一步细节。

代码：

var dataset = ee.ImageCollection('LANDSAT/LT05/C01/T1_8DAY_NDVI')
                  .filterDate('2011-01-01', '2011-12-31');
var colorized = dataset.select('NDVI');
var colorizedVis = {
  min: 0.0,
  max: 1.0,
  palette: [
    'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901',
    '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01',
    '012E01', '011D01', '011301'
  ],
};
Map.setCenter(6.746, 46.529, 6);
Map.addLayer(colorized, colorizedVis, 'Colorized');

var dataset = ee.ImageCollection('LANDSAT/LT05/C01/T1_ANNUAL_NDVI')
                  .filterDate('2011-01-01', '2011-12-31');
var colorized = dataset.select('NDVI');
var colorizedVis = {
  min: 0.0,
  max: 1.0,
  palette: [
    'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901',
    '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01',
    '012E01', '011D01', '011301'
  ],
};
Map.setCenter(6.746, 46.529, 6);
Map.addLayer(colorized, colorizedVis, 'Colorized');

var dataset = ee.ImageCollection('LANDSAT/LT05/C01/T1_32DAY_NDVI')
                  .filterDate('2011-01-01', '2011-12-31');
var colorized = dataset.select('NDVI');
var colorizedVis = {
  min: 0.0,
  max: 1.0,
  palette: [
    'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901',
    '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01',
    '012E01', '011D01', '011301'
  ],
};
Map.setCenter(6.746, 46.529, 6);
Map.addLayer(colorized, colorizedVis, 'Colorized');