2022
DOI: 10.1016/j.tfp.2021.100183
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Shifting cultivation induced burn area dynamics using ensemble approach in Northeast India

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Cited by 10 publications
(8 citation statements)
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“…In the aspect of swidden area, RdNBR_4 also showed the highest accuracy (81.33%), followed by dNBR_2 (77.67%) and by dNDVI_3 (73.55%). In previous studies, dNBR-and RdNBR-based classifications showed a higher degree of accuracy in their research results (Miller and Thode 2007;Rozario et al 2018;Miller et al 2009) and NDVI and NDVI difference also provided a great performance in capturing burned areas in Northeast India (Das et al 2022).…”
Section: Remotely Sensed Data Indices Thresholds and Models For Detec...mentioning
confidence: 84%
See 1 more Smart Citation
“…In the aspect of swidden area, RdNBR_4 also showed the highest accuracy (81.33%), followed by dNBR_2 (77.67%) and by dNDVI_3 (73.55%). In previous studies, dNBR-and RdNBR-based classifications showed a higher degree of accuracy in their research results (Miller and Thode 2007;Rozario et al 2018;Miller et al 2009) and NDVI and NDVI difference also provided a great performance in capturing burned areas in Northeast India (Das et al 2022).…”
Section: Remotely Sensed Data Indices Thresholds and Models For Detec...mentioning
confidence: 84%
“…Using remote sensing, burned areas can be mapped with various image classification methods, inclusive of visual analysis, single channel density slicing, multitemporal thresholding of vegetation indices, principal component analysis, regression modelling, supervised and unsupervised classification, and spectral mixture analysis. Recent studies identified burned forest areas of shifting cultivation using a threshold value method with great overall accuracy (Das et al 2021;Das et al 2022;. A range of spectral indices such as the Normalized Burn Ratio (NBR), the difference in the Normalized Burn Ratio between pre-and post-fire images (dNBR), and the Normalized Difference Vegetation Index (NDVI) are commonly used for producing burned area maps (Lentile et al 2006;Miller and Thode 2007;Rozario et al 2018).…”
Section: Introductionmentioning
confidence: 99%
“…The NDVI and DVI change layers were created by subtracting defoliation (leaf-off condition) from refoliation (leaf-on condition), ensuring higher positive values for RP layers than for other features. However, the opposite change, i.e., subtracting refoliation from defoliation, could misclassify RPs with deforestation or shifting cultivation in northeastern India [26,27]. This approach ensured accurate differentiation of RPs from natural or anthropogenic deforestation, such as shifting cultivation.…”
Section: Rubber Plantation Mappingmentioning
confidence: 99%
“…In India, RP development is being practiced in the warm and humid tropical climate regimes of the Western Ghats (WG) and the northeast (NE) [25]. RP mapping in the biodiversity-rich WG and NE India is essential for examining the impact of anthropogenic disturbances and native landscape management practices such as shifting cultivation [26,27]. Few studies have attempted to map the extent of RPs in WG and NE India.…”
Section: Introductionmentioning
confidence: 99%
“…Although rotational cultivation is almost the same as shifting cultivation, there are differences between both systems. In shifting cultivation, the same area is used for forestry and crop cultivation at different times (Das et al 2022). On the other hand, the rotational cultivation system can be seen as a newer stage in the evolution of farming after shifting cultivation.…”
Section: Introductionmentioning
confidence: 99%