Members’ Publication

New data platforms have made satellite data freely available and farmers can now produce variable rate application (VRA) maps for nitrogen fertilisers and other inputs based on satellite images. The data platforms are currently attracting attention for site-specific weed management because they are free and user-friendly. Satellite imagery is mainly relevant for detecting large, dense weed patches that have unique spectral characteristics in low-resolution images. The objective of this study was to examine whether Sentinel-2 images are useful in the detection of Cirsium arvense and other green vegetation in pre-harvest cereals. It was hypothesised that there is a lower limit for detection and that weeds in large patches are easier to detect than weeds in small patches. Fifteen fields infested with C. arvense were used to evaluate the possibilities of utilising the normalised difference vegetation index (NDVI) from Sentinel-2 images as a weed classifier. High-resolution RGB images from unmanned aerial vehicles (UAV) were used as ground-truthing after classifying green pixels as weeds with C. arvense as the main contributor. The study showed that C. arvense-dominated weed populations were much less aggregated than previously reported. On average, 90 % of the weeds occurred on 50 % of the field area, in a range from 21 % to 72 %. The potential herbicide savings using Sentinel-2 images were in the range of 6 % to 46 %, averaging 24 %. The low weed aggregation combined with low image resolution limited the prospects of using Sentinel-2 images for weed detection. The study showed that UAV imagery offers much greater potential for herbicide savings due to higher image resolution, allowing the detection of individual C. arvense shoots.

Comprehensive studies that employ larger data sets to explore the degree and conditions under which households depend on mangrove ecosystems account for only a negligible number in Asia's context. We contribute to these lacunae by analysing households' livelihood dependence on the Sundarbans of Asia. Specifically, we seek to: (i) appraise the livelihood strategies around the Sundarbans, (ii) analyse the conditions and determinants of household dependence on the Sundarbans, and (iii) explore perceptions surrounding livelihood dependence. An extensive survey of 1188 directly and indirectly dependent households drawn from 35 villages was conducted using structured interviews to address these topics. Twenty focus group discussions complemented this data. Using logistic regression, we analysed household dependence as a function of socioeconomic attributes. We suggest that socioeconomic factors have a substantial relationship with resource extraction and, therefore, policy prescriptions should focus on coordinating less-extractive diversification activities such as ecotourism to reduce the impact on the Sundarbans.

This research assessed the changes in spatial patterns and the seasonal trends in temperature, precipitation, and relative humidity over 36 years (1979–2014) using Climate Forecast System Reanalysis (CFSR) datasets. The evaluation of climate deviations was the prime objective of this research. The augmented Dickey–Fuller Test (ADF) was used to scrutinize whether the data was either stationary or non-stationary. The results of the ADF test showed that all the datasets were found to be stationary at lag order 3. To observe undulations in the time series data, trend analyses were done using Sen’s slope (SS), Mann–Kendall (MK), and Cox and Stuart (CS) tests. For all the statistical analyses, we considered the 5% significance level (α = 0.05) and p < 0.05 to be statistically significant. We observed significant (p < 0.05) trends in spring (MAM) and autumn (SON) for minimum temperature (Tmin) in Punjab. We also noted a significant (p < 0.05) trend in precipitation during autumn (SON). Annually, all the variables showed a non-significant (p > 0.05) trend for Punjab, Pakistan, during the period 1979–2014. Climate variability, such as a decrease in precipitation, higher temperature, and relative humidity fluctuations, were the reasons for the imbalance in the sustainability of Punjab, Pakistan

Human displacement—be it of any type, is an ancient phenomenon. It is well-known that the causes of migration are interwoven. The process is complex and holistic. Environmental degradation significantly contributes to this process. The necessity of a distinctive identity-tag for climate migrants is crucial for the proper conceptualisation of such migrants as a part of the entire migratory process. Failing to do so will leave the population in a vulnerable place to receive appropriate and adequate help. Climate-induced migration is a reality. In such a case, this paper investigates the identity formation among the displacees in an urban context. This research is mainly qualitative and adopted the in-depth interview method to understand the context of climate migrants or displacees living in the slums and squatter settlements of Khulna city. Using coding and categories, we have reviewed the information several times and have noted quotations from the interviews. We have studied the data to identify themes and concepts from the literature. This research inquires into the identity formation of the displacees and suggests that proper identification for such migrants is inevitable to ensure their entitlement to various human rights.