Validation of participatory-GIS mapping on agro-ecological landscape pursuits of cabbage farmers of Mawkynrew, East-Khasi Hills, Meghalaya using unmanned aerial vehicle : a case study.
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Date
2022-12
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College of Post Graduate Studies in Agricultural Sciences, Central Agricultural University - Imphal
Abstract
Agro-Ecological Systems research acknowledges that how systems are framed depends on the observer, making it possible to have multiple valid descriptions or conceptualizations of a system. The current study with three research objectives viz., (1) ‘To perform Participatory-GIS mapping on agro-ecological landscape of cabbage farmers’, (2) ‘To validate the attributes on agro-ecological landscape pursuits of cabbage farmers using UAV data’, and (3) ‘To estimate the agro-ecological landscape pursuits in correspondence to the predictor variables.’ has been conducted in two adopted villages of the research project—DHaBReT at Mawkynrew C&RDB of East-Khasi Hills district of Meghalaya. Descriptive research design and mixed-method sampling procedure were followed in the study. Executing Participatory GIS (PGIS) using UAV data could ascertained that high percentage of about 58% of agriculture land under cultivation had aspect toward North-East (very low unproductive sunshine) and about 85% of agricultural land is situated at a steep slope of >250, wherein administration of improved scientific agriculture was a challenge. The study could be unveiled that more than half (55.82%) of the sample respondents were female, higher percentage (45.34%) of respondents were middle aged, majority (75.58%) of the respondents had education up to high school. Cent percent of the pupils in the study were marginal farmers and had low annual income. Majority (79.06%) of them had high farming experience. Remarkably, it could be noted that the cropping intensity of all the respondents was high and majority (73.26%) of the respondents had low agricultural diversification. Further, it was observed that majority (80.23%) of the respondents had low agro-ecological landscape pursuits. On examining the validation of following three attributes derived from UAV data viz., (i) ‘Slope of Agro-Ecological Landscape’, (ii) ‘Agriculture Diversification’, and (iii) ‘Ecological Landscape Area’ with the predicted variable—‘Agro-Ecological Landscape Pursuits’. The study divulged that about thirty two percent (32.55%) of ‘Agro-Ecological Landscape Pursuit’ was truly explained by the ‘Slope of Agro-Ecological Landscape’; about forty percent (39.53%) of ‘Agro-Ecological Landscape Pursuit’ was truly explained by the ‘Agriculture Diversification’; and about seventy three (73.25%) of ‘Agro-Ecological Landscape Pursuit’ was truly explained by the ‘Ecological Landscape Area ’. Administration of binary logistic regression in order to estimate the agro-ecological landscape pursuits in correspondence to the predictor variables, revealed that 5.6% change in the predicted variable was accounted to the predictor variables in the model as supported by Nagelkerke R2 value of 0.056. The binary logistic regression model could correctly classify 80.20 % of the overall cases. The test statistic, x2 = 1.924 at p = 0.964 in Hosmer and Lemeshow test supported the model adequacy. Amongst the selected variables, it was estimated that the odds of a respondent who is having ‘Low agroecological landscape pursuits’ with ‘lower Education’ is .0968 times lower than those of ‘Higher agro-ecological landscape pursuits’ with ‘Higher farming experience’. So, is the case for ‘Agricultural Diversification’. The study strongly recommends that through participatory-GIS using UAV data the optimum spatial pattern of agriculture, forest and human settlement should be clearly developed. Analysis on land-use and land-cover change (LULCC) should be the top priority research keeping into view the encouragement of the farmers to opt for ‘Agriculture Diversification’ in order to enhance agro-ecological landscape pursuit.