Abstract
Assessment of the spatio-temporal dynamics of shifting cultivation is important to understand the opportunities for land restoration. The past studies on shifting cultivation mapping of North-East (NE) India lack systematic assessment techniques. We have developed a decision tree-based multi-step threshold (DTMT) method for consistent and long-term mapping of shifting cultivation using Landsat data from 1975 to 2018. Widely used vegetation indices such as normalized difference vegetation index (NDVI), Normalized Burn Ratio (NBR) and its relative difference NBR (RdNBR) were integrated with the suitable thresholds in the classification, which yielded overall accuracy above 85%. A significant decrease in total shifting cultivation area was observed with an overall reduction of 75% from 1975–1976 to 2017–2018. The methodology presented in this study is reproducible with minimal inputs and can be useful to map similar changes by optimizing the index threshold values to accommodate relative differences for other landscapes. Furthermore, the crop-suitability maps generated by incorporating climate and soil factors prioritizes suitable land use of shifting cultivation plots. The Google Earth Engine (GEE) platform was employed for automatic mapping of the shifting cultivation areas at desired time intervals for facilitating seamless dissemination of the map products. Besides the novel DTMT method, the shifting cultivation and crop-suitability maps generated in this study, can aid in sustainable land management.
Highlights
Shifting cultivation refers to a type of agricultural system where a patch of vegetation is cleared by the slash-and-burn method, growing assorted varieties of crops in the cleared land for a few seasons and moving to a new patch of land on a rotational basis
Accurate and periodic mapping of the shifting cultivation areas is vital for assessing their spatio-temporal dynamics for effective management of land use, and more so for the jhum-dominated landscape of northeast (NE) India
In the normalized difference vegetation index (NDVI) value range of 0.5–0.6 (NDVI_Pre _R2), the dNDVI image was categorized into three sub-classes with a threshold value of 0.35 along with the difference between pre- and post-event NBR (dNBR) threshold 9value of 16 of 0.7 and relative difference NBR (RdNBR) threshold values between 10 and 15 (Figure 5)
Summary
Shifting cultivation refers to a type of agricultural system where a patch of vegetation is cleared by the slash-and-burn method, growing assorted varieties of crops in the cleared land for a few seasons and moving to a new patch of land on a rotational basis. A crop-suitability map for NE India based on the integration of soil, climate, and physiography variables for the shifting cultivation areas would provide cropping guidance to the landholders and is not yet available. The study develops an automated method using a decision tree-based multi-step threshold to map the shifting cultivation areas at decadal interval using moderate resolution areas would provide cropping guidance to the landholders and is not yet available. The study develops an automated method using a decision tree-based multi-step threshold to map the shifting cultivation areas at decadal interval using moderate resolution satellite data. This was achieved through an evaluation study from a test site on repetition and alternation of shifting cultivation patches at different temporal4intervals.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
