Migrant remittances are potentially significant sources of funding for climate change adaptation and resilience building in developing countries. However, very little is understood about the linkages between climate actions and remittances at the household level. It is not clear how remittances can affect households’ responses to climate change. This paper presents evidence from analyses of the associations between remittances to households, their climate hazard exposure, and adaptation actors. It uses concurrent data on international remittances receipts, three climate change related hazards (flooding, intense and irregular rainfall), and main adaptation actors (self/family, community, government, and NGOs) from over 600 households in South Eastern Nigeria. The results showed that household incidence of remittances is low (15%) while exposure to climate hazards is higher (flooding: 41.2%, intense rainfall: 47.1%, irregular rainfall: 29.9%). Nominal (contingency coefficient) associations between remittances and household climate hazard exposure and remittances and household adaptation actors were mostly moderate and insignificant. Therefore, households that received remittances and those that did not were not significantly different in terms of their exposure to climate hazard and main actors in climate adaptation. Self/families were the main actors in household climate actions. Governments and NGO actors were less prominent. The results suggest that unregulated remittances have limited impact on household climate hazard exposure and adaptive actions. However, there are indications that the contribution of remittances to financing climate adaptation may be enhanced by addressing issues with cost of remitting and remittee understanding of climate change to increase remittances volumes, incidence, and use.
The availability of historical land cover data is a major challenge to long term land change analysis. This is more so in developing countries like Nigeria with weak land information systems and poor inventories of long term land cover data. This situation is to some extent ameliorated by the existence of topographic maps which represent encryptions of historical snapshots of land condition based on primary sources like aerial and land surveys. Topographic maps are however not easily amenable to analysis for land cover data extraction, given their inherent characteristics. This paper presents a GIS-based digitization, symbols analysis, pattern recognition, and polygonization methodology for the extraction of land cover information from topographic maps. The methodology is demonstrated with sheets in the Nigerian topographic map series covering the Idemili River basin. Results show that indigenous settlement types, derived Savanna, and residual forests occupied 27%, 35% and 24% of the basin area, respectively, during the period. An internal data validation approach showed a significant correlation (p = 0.000; r = 0.975) between base topographical map and extracted cover data. There is a need to apply the methodology to other topographical sheets in country's inventory to build up a national digital database of historical land cover.
KeywordsHistorical land cover • Topographic maps • GIS • Nigeria • Data validation Eine GIS-basierte Methode zum Extrahieren historischer Landbedeckungsdaten aus topographischen Karten: Eine Darstellung mit der nigerianischen Reihe topographischer Karten Zusammenfassung Die Verfügbarkeit historischer Landbedeckungsdaten ist eine große Herausforderung für die langfristige Analyse von Landveränderungen. Dies gilt insbesondere für Entwicklungsländer wie Nigeria mit schwachen Landinformationssystemen und schlechten Beständen an langfristigen Landbedeckungsdaten. Diese Situation wird in gewissem Maße durch die Existenz topographischer Karten verbessert, die historische Momentaufnahmen des Landzustands repräsentieren, die auf Primärquellen wie Luft-und Landvermessungen basieren. Topographische Karten sind jedoch aufgrund ihrer inhärenten Eigenschaften für eine Analyse zur Extraktion von Landbedeckungsdaten nicht leicht zugänglich. In diesem Artikel wird eine GIS-basierte Digitalisierungs-, Signaturenanalyse-, Mustererkennungs-und Polygonisierungsmethode zur Extraktion von Landbedeckungsinformationen aus topografischen Karten vorgestellt. Die Methodik wird anhand von Blättern der nigerianischen topographischen Kartenserie demonstriert, die das Einzugsgebiet des Flusses Idemili abdecken. Die Ergebnisse zeigen, dass einheimische Siedlungsstrukturen, abgeleitete Savannen und Restwälder im Berichtszeitraum 27%, 35% bzw. 24% der Beckenfläche einnahmen. Ein interner Datenvalidierungsansatz verweist auf eine signifikante Korrelation
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.