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    Combining Remote Sensing and Space-Time Analysis for Desertification Monitoring in the Semiarid Dryland of Nigeria

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    Desertification has been identified as the resultant effect of dryland loss. Desertification is catalysed by anthropogenic modifications and variations in environmental/climatic conditions. The situation in Nigeria is further exacerbated by the growing demand for land by the population. To this effect, this study performed a space-time analysis of vegetative cover between 2001 and 2020 to unravel patterns and trends across the semiarid region of the dryland system in Nigeria. The dynamics during the rainy season (May and September) were examined using the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) dataset subjected to space-time analysis. Generalised Difference Vegetation Index (GDVI) was computed to the power of 2 to quantify vegetative cover across the study area. The results showed that the average of the GDVI ranges between -0.40 and 0.94, with a standard deviation of 0.11. Time series cluster analysis revealed that there are two temporal clusters: (1) no statistically significant trend (Statistics= 1.33, p-value = 0.18) and (2) statistically significant downtrend (Statistics = -2.37, p=0.02), with cluster 1 covering 95% of the areas examined. The most dominant (97% of the area) emerging space-time pattern was cold-spots (persistent, diminishing, sporadic, oscillating, and historical types). In conclusion, most of the areas showed no definite temporal pattern of vegetation pattern during the period, while more than 90% of the areas have witnessed a decline in vegetative cover. There is a need for a more coordinated approach to desertification control, constant monitoring is pertinent while new approaches to restoring degraded land are recommended

    Application of decomposition techniques in a wildfire suppression optimization model

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    Resource assignment and scheduling models provides an automatic and fast decision support system for wildfire suppression logistics. However, this process generates challenging optimization problems in many real-world cases, and the computational time becomes a critical issue, especially in realistic-size instances. Thus, to overcome that limitation, this work studies and applies a set of decomposition techniques such as augmented Lagrangian, branch and price, and Benders decomposition’s to a wildfire suppression model. Moreover, a reformulation strategy, inspired by Benders’ decomposition, is also introduced and demonstrated. Finally, a numerical study comparing the behavior of the proposals using different problem sizes is conductedThis research work is supported by the R+D+I project grants PID2020-116587GB-I00 and PID2021-124030NB (C31 and C32), funded by MCIN/AEI/10.13039/501100011033/ and by “ERDF A way of making Europe”/EU. Second author investigation is funded by the Xunta de Galicia (contract post-doctoral 2019-2022). We acknowledge the computational resources provided by CESGA. Third author acknowledges support from the Xunta de Galicia through the ERDF (ED431C-2020-14 and ED431G 2019/01), and “CITIC”S

    Farmer perception of benefits, constraints and opportunities for silvoarable systems: preliminary insights from Bedfordshire, England

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    Silvoarable agroforestry integrates the use of trees and arable crops on the same area of land, and such systems can be supported by national governments under the European Union’s (EU) Rural Development Regulations (2014–2020). In order to improve the understanding of farmers’ perceptions of such systems, detailed face-to-face interviews were completed with 15 farmers in Bedfordshire, England. Most of these farmers thought that silvoarable systems would not be profitable on their farms and that benefits would tend to be environmental or social rather than economic. Most farmers also thought that management and use of machinery would become more difficult. They felt that the tree component could potentially disrupt field operations and drainage and expressed concerns over the uncertain and long-term nature of timber revenue and the effect of intercrop yield reductions on crop revenue. Even so, 20% of the farmers stated they would use silvoarable systems if convinced that they were more profitable than conventional arable farming. A further 20% said they would farm the intercrop area belonging to someone else, if the rent was reduced to compensate for crop yield reductions. These results suggest that for most arable farmers, an economic advantage over current practice needs to exist before silvoarable systems are likely to be adopted. However, a minority might rent the crop component of a silvoarable system from another party or implement a full system for perceived environmental or social benefits
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