Google Earth Engine（GEE）——计算ndvi的零星植被状况（墨西哥为例）

举报
此星光明 发表于 2022/06/13 11:10:17 2022/06/13
【摘要】 ​本文使用Landsat7影像来计算ndvi的零星植被状况并查看影像的温度，这里面要特别注意不同的影像集合中波段名称是不同的，所以建议要认真查看波段，这里再次列举一下本次要用到的影像波段，特别注意去云波段：Resolution30 metersBands TableNameDescriptionMinMaxUnitsWavelengthScaleOffsetSR_B1Band 1 (blue...

​

本文使用Landsat7影像来计算ndvi的零星植被状况并查看影像的温度，这里面要特别注意不同的影像集合中波段名称是不同的，所以建议要认真查看波段，这里再次列举一下本次要用到的影像波段，特别注意去云波段：

Resolution

30 meters

Bands Table

Name Description Min Max Units Wavelength Scale Offset
SR_B1 Band 1 (blue) surface reflectance 1 65455 0.45-0.52 μm 0.0000275 -0.2
SR_B2 Band 2 (green) surface reflectance 1 65455 0.52-0.60 μm 0.0000275 -0.2
SR_B3 Band 3 (red) surface reflectance 1 65455 0.63-0.69 μm 0.0000275 -0.2
SR_B4 Band 4 (near infrared) surface reflectance 1 65455 0.77-0.90 μm 0.0000275 -0.2
SR_B5 Band 5 (shortwave infrared 1) surface reflectance 1 65455 1.55-1.75 μm 0.0000275 -0.2
SR_B7 Band 7 (shortwave infrared 2) surface reflectance 1 65455 2.08-2.35 μm 0.0000275 -0.2
SR_ATMOS_OPACITY A general interpretation of atmospheric opacity generated by LEDAPS and based on the radiance viewed over Dark Dense Vegetation (DDV) within the scene. A general interpretation of atmospheric opacity is that values (after scaling by 0.001 is applied) less than 0.1 are clear, 0.1-0.3 are average, and values greater than 0.3 indicate haze or other cloud situations. SR values from pixels with high atmospheric opacity will be less reliable, especially under high solar zenith angle conditions. The SR_ATMOS_OPACITY band is provided for advanced users and for product quality assessment and has not been validated. Most users are advised to instead use the QA_PIXEL band information for cloud discrimination. 0 10000 0.001 0
SR_CLOUD_QA Cloud Quality Assessment 0 0
SR_CLOUD_QA Bitmask
  • Bit 0: Dark Dense Vegetation (DDV)
    • Bit 1: Cloud
      • Bit 2: Cloud Shadow
        • Bit 3: Adjacent to Cloud
          • Bit 4: Snow
            • Bit 5: Water
              ST_B6 Band 6 surface temperature. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 65535 Kelvin 10.40-12.50 μm 0.00341802 149
              ST_ATRAN Atmospheric Transmittance. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 10000 0.0001 0
              ST_CDIST Pixel distance to cloud. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 24000 km 0.01 0
              ST_DRAD Downwelled Radiance. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 28000 W/(m^2*sr*um)/ DN 0.001 0
              ST_EMIS Emissivity estimated from ASTER GED. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 10000 0.0001 0
              ST_EMSD Emissivity standard deviation. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 10000 0.0001 0
              ST_QA Uncertainty of the Surface Temperature band. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 32767 K 0.01 0
              ST_TRAD Thermal band converted to radiance. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 22000 W/(m^2*sr*um)/ DN 0.001 0
              ST_URAD Upwelled Radiance. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out. 0 28000 W/(m^2*sr*um)/ DN 0.001 0
              QA_PIXEL Pixel quality attributes generated from the CFMASK algorithm. 0 0
              QA_PIXEL Bitmask
              • Bit 0: Fill
                • Bit 1: Dilated Cloud
                  • Bit 2: Unused
                    • Bit 3: Cloud
                      • Bit 4: Cloud Shadow
                        • Bit 5: Snow
                          • Bit 6: Clear
                            • 0: Cloud or Dilated Cloud bits are set
                            • 1: Cloud and Dilated Cloud bits are not set
                          • Bit 7: Water
                            • Bits 8-9: Cloud Confidence
                              • 0: None
                              • 1: Low
                              • 2: Medium
                              • 3: High
                            • Bits 10-11: Cloud Shadow Confidence
                              • 0: None
                              • 1: Low
                              • 2: Medium
                              • 3: High
                            • Bits 12-13: Snow/Ice Confidence
                              • 0: None
                              • 1: Low
                              • 2: Medium
                              • 3: High
                            • Bits 14-15: Cirrus Confidence
                              • 0: None
                              • 1: Low
                              • 2: Medium
                              • 3: High
                            QA_RADSAT Radiometric saturation QA 0 0
                            QA_RADSAT Bitmask
                            • Bit 0: Band 1 data saturated
                              • Bit 1: Band 2 data saturated
                                • Bit 2: Band 3 data saturated
                                  • Bit 3: Band 4 data saturated
                                    • Bit 4: Band 5 data saturated
                                      • Bit 5: Band 6L data saturated
                                        • Bit 6: Band 7 data saturated
                                          • Bit 7: Unused
                                            • Bit 8: Band 6H data saturated
                                              • Bit 9: Dropped pixel
                                                • 0: Pixel present
                                                • 1: Detector doesn't have a value


                                              代码：

                                              获取的最大最小值的结果： 这里用的是.values().get(0),也就是第一个值

                                              ​

                                              结果：

                                              ​代码链接：

                                              (179条消息) Google Earth Engine（GEE）——计算ndvi的零星植被状况（墨西哥为例）_此星光明2021年博客之星云计算Top3的博客-CSDN博客

                                              往期推荐：

                                              Google Earth Engine（GEE）——自动化制作30米Landsat影像和土地分类（只需要输入研究区路径）

                                              Google Earth Engine ——Landsat 5 TM合成影像8天/32天/年际增强植被指数（EVI）数据集

                                              Google Earth Engine ——Landsat 5 TM合成影像8天/32天/年际烧伤面积指数（BAI）

                                              Google Earth Engine ——LANDSAT8系列归一化植被指数NDVI数据集

                                              Google Earth Engine ——全球JRC/GSW1_3/MonthlyHistory数据集的观测数据

                                              Google Earth Engine ——全球1984年至2015年地表水的位置和时间即地表水数据集的观测数据的元数据

                                              【版权声明】本文为华为云社区用户原创内容，转载时必须标注文章的来源（华为云社区）、文章链接、文章作者等基本信息， 否则作者和本社区有权追究责任。如果您发现本社区中有涉嫌抄袭的内容，欢迎发送邮件进行举报，并提供相关证据，一经查实，本社区将立刻删除涉嫌侵权内容，举报邮箱： cloudbbs@huaweicloud.com
                                              • 点赞
                                              • 收藏
                                              • 关注作者

                                              评论（0）

                                              0/1000
                                              抱歉，系统识别当前为高风险访问，暂不支持该操作

                                              全部回复

                                              上滑加载中

                                              设置昵称

                                              在此一键设置昵称，即可参与社区互动！

                                              *长度不超过10个汉字或20个英文字符，设置后3个月内不可修改。

                                              *长度不超过10个汉字或20个英文字符，设置后3个月内不可修改。

                                              确认 取消

                                              加入云驻计划，成为创作者

                                              • 华为云周边好礼
                                              • 免费体验产品
                                              • 特殊身份标识
                                              • 线下官方门票
                                              • 内部专家零距离
                                              • 与10000+优质创作者共同成长
                                              立即加入