Dataset for "A Global Systematic Review of Improving Crop Model Estimations by Assimilating Remote Sensing Data: Implications for Small-Scale Agricultural Systems"
Dataset
categories
- Artificial Intelligence and Image Processing
- Other Environmental Sciences
- Physical Geography and Environmental Geoscience
- Crop and Pasture Production
- Other Earth Sciences
- Earth Sciences
- Agricultural and Veterinary Sciences
- Plant Production and Plant Primary Products
- Information and Computing Sciences
- Environmental Sciences
time coverage
1 January 2011 - 31 July 2021
licence
CC0
We conducted a systematic review of research on data assimilation and summarized how its application varies by country, crop, and farming systems. In addition, we highlight the implications of using process-based crop models (PBCMs) and data assimilation in small-scale farming systems. Using a strict search term, we searched the Scopus and Web of Science databases and found 497 potential publications. After screening for relevance using predefined inclusion and exclusion criteria, 123 publications were included in the final review and are shared in this data.
history
publisher
4TU.ResearchData
format
Excel spreadsheet
associated peer-reviewed publication
A Global Systematic Review of Improving Crop Model Estimations by Assimilating Remote Sensing Data: Implications for Small-Scale Agricultural Systems
derived from
funding
- NRF-NUFFIC Doctoral Scholarship [more info...] National Research Foundation South Africa
organizations
University of Cape Town, Wageningen University & Research
DATA
files (1)
-
85,346 bytesMD5:
5e21e20a4576a3eac0894298ad79cf88Global systematic review_LD.xlsx - download all files (zip)
85,346 bytes unzipped
