The rise of the population in developing countries has increased significantly in recent decades. Small farmers (2 hectares or less) total half the population in the rural regions of developing countries. The crops harvested by these farmers total 90% of their nations food staples.
Unfortunately, small farmers are vulnerable to drought, market instability and climate change. Unlike large farms in developed nations, small farmers do not have access to funding, technology or nutrient for their crops. Therefore, these farms are being monitored using satellite imagery and GIS software to ensure a successful harvest or face a possible famine.
There are three different methods that can be used to measure the size and density of farms and their crops: high-resolution images, Landsat and Modi. Even with these programs and satellite images measuring the correct size of these farms has proved to be difficult. In order to get an accurate measurement all three methods need to be used to analyze the crops and the environment surrounding them.
The authors studied Gujart and Madhya Pradesh in India using all three methods to get accurate information. The diagram below shows the data collected from both regions. It shows that scientists cannot get an accurate reading of a region solely relying on one technique and exclude the others.
It shows that high-resolution images, Landsat and Modi have their strengths and limitations but when combined it can be accurate. With an ever-growing world population the need for food sustainability and food security has become a priority.
Jain, M., Mondal, P., DeFries, R. S., Small, C., & Galford, G. L. (2013). Mapping cropping intensity of smallholder farms: A comparison of methods using multiple sensors. Remote Sensing of Environment, 134, 210-223.