QX/T 494-2019 in English
VALIDGrade of monitoring and evaluating for terrestrial vegetation meteorology and ecological quality
- Issued on:2019-09-18
- Implemented on:2019-12-01
- File Format:PDF
- Delivery:Via email within 1~3 business days
$243.00
本标准规定了陆地植被生长气象条件和植被覆盖度、植被净初级生产力、植被生态质量的监测评价方法及等级。本标准适用于全年或生长季陆地植被生长气象条件和植被生态质量的监测评价。
Introduction
Standard Background and Technological Evolution
As an industry-specific specification of GB/T 34815-2017 "Meteorological Evaluation Index of Vegetation Ecological Quality", this standard innovatively combines satellite remote sensing data such as NOAA/AVHRR and EOS/MODIS with ground meteorological observations to construct a comprehensive evaluation system including 3 meteorological factors (heat, moisture, sunshine) and 2 ecological parameters (coverage, NPP).
Core monitoring indicator system
| Indicator type | Calculation parameters | Evaluation dimension | Data source |
|---|---|---|---|
| Meteorological condition index | Accumulated temperature anomaly rate, precipitation anomaly rate, sunshine anomaly rate | Interannual variation | Ground observation station |
| Vegetation coverage | NDVI value, soil baseline value | Spatial distribution | Satellite remote sensing |
| Net primary productivity | Light energy conversion rate, respiratory consumption coefficient | Carbon sink capacity | Model inversion |
Analysis of grading evaluation method
3.2.1 Evaluation of thermal conditions
The activity accumulated temperature deviation percentage (ΔT) is used for grading. When ΔT≥10%, it is evaluated as "very good". Calculation formula:
$$\Delta T=(\sum_{j=1}^{n}t_{j}-\overline{T})/\overline{T}\times100\%$$
3.4 Evaluation of net primary productivity
NPP is divided into 6 levels, and ≥1000g/m² is the "very high" level. The interannual comparison uses the anomaly percentage method:
$$\Delta NPP=(NPP-\overline{NPP})/\overline{NPP}\times100\%$$
Implementation suggestions
Data quality control:It is recommended to use more than 10 years of benchmark data to calculate the annual value. When inverting NDVI, the radiation calibration parameters of the MODIS and FY-3 sensors need to be unified.
Regional adaptation:The weight coefficients (f₁, f₂) in the ecological quality index should be adjusted according to the vegetation type. For example, the NPP weight can be increased to 0.6 in forest areas.
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