سابِق|تال

Verification and analysis of high spatial-temporal resolution vegetation index product based on GF-1 satellite data

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

  • Email：zhangzhaoxing@aircas.ac.cn
  • Introduction：张召星，研究方向为植被定量遥感、作物生长模型与遥感同化。E-mail：zhangzhaoxing@aircas.ac.cn
ZHANG Zhaoxing1,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：lijing01@radi.ac.cn
  • Introduction：李静，研究方向为植被辐射传输模型、叶面积指数反演。E-mail：lijing01@radi.ac.cn
LI Jing12*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

LIU Qinhuo12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

ZHAO Jing1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

DONG Yadong1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

LI Songze12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

WEN Yuan12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

YU Wentao1

ملخص

The rapid development of remote sensing technology has promoted the generation of different vegetation index products. Normalized Difference Vegetation Index (NDVI) is the vegetation index with the highest utilization rate. However, the existing NDVI products have insufficient time resolution and spatial resolution, thereby limiting the fine dynamic monitoring application in a certain region. The Wide-Field View (WFV) of GF-1 satellite data has a 4-day revisit period and 16 m spatial resolution, indicating its great potential in long-time series dynamic monitoring. The objective of this study is to establish a method for generating a 16 m/10-day NDVI product based on GF-1 images from 2018 to 2020.In this study, the GF-1 NDVI products of 16 m and 10 days from 2018 to 2020 are produced based on GF-1 WFV. Moreover, Landsat NDVI and sentinel-2 NDVI products are produced based on landsat7, landsat8, and sentinel-2 data in the Google Earth engine database. The quantitative analysis and evaluation of time, spatial consistency, spatial continuity, and product comparison are performed from the space and time scale.In January and August, the spatial distribution of MuSyQ NDVI, Landsat NDVI, and sentinel-2 NDVI products in China is reasonable and consistent. MuSyQ NDVI’s lack of space in January is lower than that of two other products. The frequency distribution histogram of MuSyQ NDVI, Landsat NDVI, and sentinel-2 NDVI differs. The difference among the three products is concentrated in the range of ±0.2, the peak value is at 0, and the frequency is close to 70%. These findings indicate that MuSyQ NDVI has good spatial consistency with the two other NDVI products. In Northeast China, Northwest China, and Qinghai Tibet Plateau, MuSyQ NDV has a lower loss rate and better spatial continuity than the two other products. Moreover, the spatial continuity of products is high. On the whole, the effective value ratio of the MuSyQ NDVI product is better than that of the two other products; in particular, the effective value ratios of the MuSyQ NDVI product in farmland and grassland areas are 28.6 (70%) and 30.27 (70%), respectively, which are higher than those of the two other NDVI products. In the forest area, the effective value ratio of MuSyQ NDVI is also slightly better than that of the two other products. The three NDVI products have good consistency and phenological characteristics in the time series of farmland and grassland. In the deciduous broad-leaved forest area, the three products have similar seasonal variation laws. They fluctuate greatly in the time series curve in the evergreen broad-leaved forest and evergreen coniferous forest area. The consistency of MuSyQ NDVI, Landsat NDVI, and sentinel-2 NDVI in nonforest sites is higher than that in forest sites.In terms of spatial and temporal scales, the high spatial-temporal resolution NDVI products provided by GF-1/NDVI products are better than the existing products. They also provide useful information for selecting NDVI products in subsequent vegetation dynamic research. Moreover, they have advantages for long-time series fine monitoring in an extensive spatial range.

مفهوم

GF-1;vegetation index;high resolution;spatiotemporal characteristics;cross validation

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