From pixels to patterns: review of remote sensing techniques for mapping shifting cultivation systems

Shifting agriculture is a complex system requiring organized categorization and measurement due to its widespread practice in tropics and impact on greenhouse gases. Remote sensing technologies and participatory mapping drive efforts to map these areas. This study provides a methodological overview of mapping techniques used for shifting cultivation from 2000 to present, covering local to global studies, identifying trends in remote sensing-based estimation of spatio-temporal patterns in these landscapes. Spatial resolution, classification method, ground truthing and data collection frequency were found to be important factors in mapping these mosaics. While most studies originate from Asia, there are also significant contributions from the Americas and Africa. Highlighting the intricacy of these systems, techniques such as spectral indices, cultivation stage differentiation, time-series data, and agent-based modeling have been used. Ground truthing from various sources validates and ensures accuracy. Other methods like object-based analysis, participatory approaches, image differencing, and neural networks also enhance comprehension of these areas. These insights will benefit related studies for assessing these landscapes at varying scales to enhance their management. Further collaborative research is essential to create automated methods and consistent protocols for monitoring these systems.