An index of non-sampling error in area frame sampling based on remote sensing data.

Area of Science:

• Agricultural Science
• Remote Sensing
• Survey Methodology

Background:

• Area frame sampling is standard for agricultural surveys.
• Non-updated sampling frames lead to significant non-sampling errors due to land use changes.
• Accurate crop area statistics are crucial for agricultural management and policy.

Purpose of the Study:

• To propose a novel method for estimating non-sampling errors in crop area statistics caused by land use changes.
• To introduce a new index, the non-sampling error by land use change index (NELUCI), for error estimation.
• To improve the accuracy of agricultural area estimations.

Main Methods:

• Utilized satellite remote sensing imagery to monitor changes in land cover and usage.
• Tracked three key stratified sampling parameters: total sampling units, units per stratum, and mean values per stratum.
• Defined and applied the non-sampling error by land use change index (NELUCI).

Main Results:

• The novel method successfully estimated cropping area sizes in Bole, Xinjiang, China.
• Achieved a coefficient of variation of 0.0237 and a NELUCI of 0.0379.
• Demonstrated significant reductions in errors (0.0474 and 0.0994) compared to traditional methods.

Conclusions:

• The proposed method effectively estimates non-sampling errors arising from land use changes in agricultural surveys.
• The NELUCI provides a reliable metric for quantifying these errors.
• This approach enhances the accuracy and reliability of crop area statistics derived from remote sensing and sampling techniques.