Google Earth Engine——NOAA/DMSP-OLS/NIGHTTIME_LIGHTS,DMSP数据由美国空军气象局收集

The Defense Meteorological Program (DMSP) Operational Line-Scan System (OLS) has a unique capability to detect visible and near-infrared (VNIR) emission sources at night.

Version 4 of the DMSP-OLS Nighttime Lights Time Series consists of cloud-free composites made using all the available archived DMSP-OLS smooth resolution data for calendar years. In cases where two satellites were collecting data, two composites were produced.

Image and data processing by NOAA's National Geophysical Data Center. DMSP data collected by US Air Force Weather Agency.

国防气象计划(DMSP)的作业线扫描系统(OLS)具有独特的能力,可以探测夜间的可见和近红外(VNIR)发射源。

DMSP-OLS夜间灯光时间序列的第4版包括使用历年所有可用的DMSP-OLS平滑分辨率存档数据进行的无云合成。在有两颗卫星收集数据的情况下,就会产生两个合成物。

图像和数据处理由NOAA的国家地球物理资料中心进行。DMSP数据由美国空军气象局收集。

Dataset Availability

1992-01-01T00:00:00 - 2014-01-01T00:00:00

Dataset Provider

Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines

Collection Snippet

ee.ImageCollection("NOAA/DMSP-OLS/NIGHTTIME_LIGHTS")

Resolution

927.67 meters

Bands Table

NameDescriptionMin*Max*
avg_visThe average of the visible band digital number values with no further filtering.063
stable_lightsThe cleaned up avg_vis contains the lights from cities, towns, and other sites with persistent lighting, including gas flares. Ephemeral events, such as fires, have been discarded. The background noise was identified and replaced with values of zero.063
cf_cvgCloud-free coverages tally the total number of observations that went into each 30-arc second grid cell. This band can be used to identify areas with low numbers of observations where the quality is reduced.0126
avg_lights_x_pctThe average visible band digital number (DN) of cloud-free light detections multiplied by the percent frequency of light detection. The inclusion of the percent frequency of detection term normalizes the resulting digital values for variations in the persistence of lighting. For instance, the value for a light only detected half the time is discounted by 50%. Note that this product contains detections from fires and a variable amount of background noise.063

* = Values are estimated

数据说明:

NOAA data, information, and products, regardless of the method of delivery, are not subject to copyright and carry no restrictions on their subsequent use by the public. Once obtained, they may be put to any lawful use. The forgoing data is in the public domain and is being provided without restriction on use and distribution.

代码:

var dataset = ee.ImageCollection('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS')
                  .filter(ee.Filter.date('2010-01-01', '2010-12-31'));
var nighttimeLights = dataset.select('avg_vis');
var nighttimeLightsVis = {
  min: 3.0,
  max: 60.0,
};
Map.setCenter(7.82, 49.1, 4);
Map.addLayer(nighttimeLights, nighttimeLightsVis, 'Nighttime Lights');

以下是根据您的要求编写的 Google Earth Engine 代码: ```javascript // 选择研究区,以山西省为研究区 var region = ee.FeatureCollection("users/your_username/your_feature_collection") .filter(ee.Filter.eq('province', '山西省')); // 定义起始时间终止时间 var startDate = ee.Date('2000-01-01'); var endDate = ee.Date('2020-12-31'); // 加载NDVI影像 var ndviCollection = ee.ImageCollection('MODIS/006/MOD13Q1') .select('NDVI') .filterBounds(region) .filterDate(startDate, endDate); // 加载降水影像 var precipitationCollection = ee.ImageCollection('NASA/GPM_L3/IMERG_V06') .select('precipitationCal') .filterBounds(region) .filterDate(startDate, endDate); // 加载气温影像 var temperatureCollection = ee.ImageCollection('MODIS/006/MYD11A2') .select('LST_Day_1km') .filterBounds(region) .filterDate(startDate, endDate); // 加载夜间灯光数据影像 var nightLights = ee.ImageCollection("NOAA/DMSP-OLS/NIGHTTIME_LIGHTS") .select("avg_vis") .filterBounds(region) .filterDate(startDate, endDate); // pearsonsCorrelation计算相关性系数 var correlation = ndviCollection .addBands(precipitationCollection) .addBands(temperatureCollection) .addBands(nightLights) .reduce(ee.Reducer.pearsonsCorrelation()) .clip(region); // 在这里,对堆栈进行采样 var sample = correlation.sample({ region: region, scale: 1000, numPixels: 1000 }); // 正确调用reducer var stats = sample.reduceColumns({ selectors: ['NDVI', 'precipitationCal'], reducer: ee.Reducer.mean() }); // 然后选择两个属性以查看相关性 var ndviMean = stats.get('mean_NDVI'); var precipitationMean = stats.get('mean_precipitationCal'); print('Mean NDVI:', ndviMean); print('Mean Precipitation:', precipitationMean); // 导出函数 Export.table.toDrive({ collection: sample, description: 'correlation_sample', fileFormat: 'CSV' }); ``` 请确保将代码中的`your_username`替换为您的用户名,并根据您的需求进行其他适当的更改。此代码将加载山西省内的NDVI、降水、气温夜间灯光数据影像,并计算它们之间的相关性系数。然后,对相关性结果进行采样,并计算NDVI降水的平均值。最后,将采样结果导出为CSV文件。
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