Shifting Cultivation and Geospatial Technology

"Tree makes one million matchsticks, but one match-stick can burn one million trees"

Shifting Cultivation

This is a system of farming where a piece of land is cleared followed by several years of wood harvesting or farming until the soil loses fertility. Once the land becomes inadequate for crop production, it is left to be reclaimed by natural vegetation. Across south and southeast Asia, a large number of people depend fully or partly on shifting cultivation for their livelihood and food security and a common practice in north east India.

 
                                              Forest area cleared for shifting cultivation

This is a traditional and very old way of farming which is no longer relevant because of the large population and its growing demands. This is sometimes also called rotational farming, swidden farming/agriculture or slash-and-burn agriculture.

Is it a good or bad practice of farming?

This is a controversial form of land use. Some considered it as the most serious land use problem in tropical world. For more than a century, colonial and post-colonial governments in Asia have devised policies and laws to eradicate shifting cultivation, in the name of forest conservation and development. Some considered it as an economically inefficient and ecologically harmful practice. It was an ideal solution for agriculture in the humid tropics as long as the human population density was not too high and fallow periods are long enough to restore soil fertility. This agricultural system is ecologically sound and meets a variety of human needs with great efficiency, particularly with regard to labour and other agricultural inputs.

The current climate change discourse has taken the debate on shifting cultivation to a global level: now they are blamed for causing too much carbon emissions, and thus for contributing to global warming. In a nut shell we can say it is good if a population depending on it is limited.

Remote sensing approach – Temporal and spatial dynamics

This is a time series based approach to detect land cover change and retrieve the frequency of slash-and-burn events and the length of fallow periods over time. Along with land cover classification and bi-temporal changes these methods are useful for detecting major changes in deforestation and the spatial distribution of different land cover classes. Temporal data from remote sensing is used to evaluate how fallow period and expansion over old-growth forest changed over time, and how land use patterns are related to land accessibility and human population density.

 
                                     Forest turn into cultivation land

Detection of slash and burn plots

It is not easy to detect slash and burn plots by spectral classification of satellite imageries. There are so many similar spectral characteristics like old logging site, site of forest fire, site of landslide and debris flow, site of factory or housing development, facility area etc. for this reason different image processing algorithms and tools are adopted that include various index's used like NBR (Normalized Burn Ratio), BAI (Burn Area Index) SAVI (Soil Adjust Vegetation Index), NDVI (Normalized Different Vegetation Index), NDMI (Normalized Different Moist Index) etc.  

 

Role of Digital Elevation Model (DEM)

Digital elevation model (DEM) is a potential tool for terrain analysis at varied spatial and temporal scales. It is used to generate slope information for regenerating shifting cultivation areas in different slope conditions. One of the most useful properties of DEMs is the ability to reclassify datasets. For example, slope, aspect and elevation can be classified to meet requirements or parameters of landscape components.

Summery

Across south and southeast Asia, a large number of people depend fully or partly on shifting cultivation. This is sometimes also called rotational farming, swidden farming/agriculture or slash-and-burn agriculture. Remote sensing, GIS and photogrammetry technology is contributing in the study of this type of cultivation. Image processing and various index's are used like NBR, NDVI, NDMI, etc. DEM is also important for the classification and terrain analysis at varied spatial and temporal scales.