Menu Close Toggle Nav Notebook Notebook
Menu
Account
Search
Search Close Enter a search term
Advanced Search

Unique ID: 2015026

Division: Research Institute of Statistical Science
Issue Date: February 13th 2019
Last modified: February 22nd 2019
Be first to add a comment
Cost: FREE
Add to Notebook
Collaborative

Crop survey by farmland: using satellite and aerial remote sensing to help estimate agricultural statistics

Using satellite and aerial remote sensing to help estimate agricultural statistics

Build up the spatial sampling frame by using the data from land use surveys and agricultural census. Then update the sampling frame by satellite and aerial remote sensing. With the samples selected by spatial sampling method, we estimate the crop planting area and output every season.

Project Objective:

Pilot intended to go to production to replace existing data

Project Outcomes:

Gradually carry forward the crops survey by farmland instead of the traditional method used in China's major grain-producing areas to improve the accuracy, timeliness and consistency of the data to ensure data quality.

Statistical Area

Agriculture (including Food Security)

Project Sources
Project Sources
Type Of Institution: National statistical office
Big Data Source: Satellite imagery or aerial imagery data
Region: East Asia & Pacific
Country Area: China
Id Country Regional: country
Partnerships
Partnerships
Data Providers: Satellite or aerial imagery provider
Other Partners: Government institute
Accessing Data
Accessing Data
Data Access Rights: Broader access rights
Data Coverage
Data Coverage
Data Coverage: Only a portion of all data
Coverage Geo Pop: Part of country / low % of market
Cost Implication: Commercial
Coverage Period: Some fixed time intervals every year
Data Quality
Data Quality
Quality Framework: Quality of processing/throughput
Quality Aspects Evaluated: Privacy and Security, Completeness, Usability, Time Factors, Accessibility, Relevance, Coherence, including linkability to other sources
Methodology
Methodology
Methods Used: Traditional statistical methods, Supervised learning, Decision Trees
Technologies
Technologies
Technologies: GIS, Relational database
Other
Other
Income Level: Upper-middle-income
Iso: CN
Timeframe To Produce Indicator: NA
Write Your Own Review
You're reviewing:Crop survey by farmland: using satellite and aerial remote sensing to help estimate agricultural statistics
Your Rating