This study examined the physical properties of agricultural drought (i.e., intensity, duration, and severity) in Hungary from 1961 to 2010 based on the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The study analyzed the interaction between drought and crop yield for maize and wheat using standardized yield residual series (SYRS), and the crop-drought resilient factor (CDRF). The results of both SPI and SPEI (-3, -6) showed that the western part of Hungary has significantly more prone to agricultural drought than the eastern part of the country. Drought frequency analysis reveals that the eastern, northern, and central parts of Hungary were the most affected regions. Drought analysis also showed that drought was particularly severe in Hungary during 1970–1973, 1990–1995, 2000–2003, and 2007. The yield of maize was more adversely affected than wheat especially in the western and southern regions of Hungary (1961–2010). In general, maize and wheat yields were severely non-resilient (CDRF < 0.8) in the central and western part of the country. The results suggest that drought events are a threat to the attainment of the second Sustainable Development Goals (SDG-2). Therefore, to ensure food security in Hungary and in other parts of the world, drought resistant crop varieties need to be developed to mitigate the adverse effects of climate change on agricultural production.

This article presents the clearest description to date concerning how to compute the hypothetical classification errors that could explain deviations from uniform land changes in the context of Intensity Analysis. Intensity Analysis is an accounting framework that analyses a square contingency table to measure how the sizes of the changes compare to the sizes of the categories. Our case study analyses maps of a portion of southern Nigeria at 1987 and 2002 that show the categories: cultivation, forest, settlement, and water. The data reveal that the changes are not uniformly proportional to the sizes of the categories in terms of categorical gains, categorical losses, and transitions. The methods in this article show that hypothetical error in 9% of the 2002 map could explain all the deviations from uniform categorical gains, hypothetical error in 11% of the 1987 map could explain all the deviations from uniform categorical losses, and hypothetical error in 6% of the 1987 map could explain all deviations from uniform transitions. Larger hypothetical error indicates stronger evidence for a particular deviation from the relevant hypothesized uniform intensity. It is helpful to know the strength of evidence, even when the actual errors in the maps are unknown, which is frequently the case for historical time points.

This study determined pre-conflict, conflict and post-conflict land use change and analysed the impact of armed conflict on the intensity of land use change in northern Nimba County. Landsat images of 1986, 1990, 2002 and 2016 were classified into four dominant land use categories in the study area: cultivation, mine, forest and settlement using maximum likelihood classification algorithm. Land use change was determined by deriving pre-conflict, conflict and post-conflict transition matrix. Based on the transition matrix, gain, loss, persistence, total change, swap and absolute value of net change were computed. Intensity of land use change was determined using the intensity analysis approach. The results show that the intensity of land use change was slow during the conflict but increased sharply after the conflict. Pre-conflict, conflict and post-conflict mine occupied 0.63%, 0.78% and 17.68%, forest cover accounted for 71.08%, 69.26% and 56.42% and settlement was 1.99%, 1.96% and 25.63% respectively. Similarly, pre-conflict, conflict and post-conflict uniform intensity of land use change was 4.09%, 1.51% and 5.01% respectively. Recent forest cover loss is primarily driven by sustained settlement expansion. The implications of rapid post-conflict settlement increase and forest loss in northern Nimba County include threat to habitat in a globally important biodiversity hotspot, increasing pressure on available agricultural land because of increasing population and potential exposure of the population to pollution from increase in mining activities. Therefore, more effective forest management strategies need to be developed to mitigate the prevailing trend. The use of intensity analysis has provided insights on the patterns and processes of pre-conflict, conflict and post-conflict land use change in a biodiversity hotspot. This is important for defining effective conservation goals, planning sustainable conservation strategies and deploying relevant tools for forest conservation and governance in conflict and conflict prone areas.

This study examines the pattern and processes of land-use change in a densely populated coastal city in the oil-rich Niger Delta region of Nigeria for 27 years using remote sensing and Geographic Information Systems. The results indicate that between 1986 and 2013, settlement/bare surface, mangrove forest/wetland and water body increased at 0.84% per year, 0.05% per year and 0.10% per year, respectively, while arable land/secondary vegetation and natural forest loss at 0.47% per year and 0.52% per year, respectively. This implies that intensity of change varies temporally. The implications of these changes include loss of valuable environmental goods and services, alteration of the food chain and increased impacts of climate change–related disasters. It is recommended that steps be taken to slow down the rate of land-use change in the study area to reduce its impact on the environment and social well-being.

This study examines deforestation in a part of the Niger Delta region of Nigeria between 1987 and 2013 using remote sensing data and geographic information systems. The results indicate an increasing rate of deforestation, an increasing rate of water body loss and a decreasing rate of exposed surface/settlement increase. The results also show that the rate at which cropland/secondary vegetation is increasing is above average while sandbar is increasing below average. The implications of these changes include environmental degradation resulting from loss of biodiversity and loss of forest goods and services. These losses can also affect the social and economic conditions of local people. The study recommends that policies and strategies targeted at slowing down the rate of forest loss and degradation should be pursued.