Estimation of herbaceous fuel moisture content using vegetation indices and land surface temperature from MODIS data

The monitoring of herbaceous fuel moisture content is a crucial activity in order to assess savanna fire risks. Faced with the difficulty of managing wide areas of vegetated surfaces, remote sensing appears an attractive alternative for terrestrial measurements because of its advantages related to temporal resolution and spatial coverage. Earth observation (EO)-based vegetation indices (VIs) and the ratio between Normalized Difference Vegetation Index (NDVI) and surface temperature (ST) were used for assessment of herbaceous fuel moisture content estimates and validated against herbaceous data collected in 2010 at three open savanna sites located in Senegal, West Africa. EO-based estimates of water content were more consistent with the use of VI as compared to the ratio NDVI/ST. Different VIs based on near-infrared (NIR) and shortwave infrared (SWIR) reflectance were tested and a consistent relationship was found between field measurements of leaf equivalent water thickness (EWT) from all test sites and Normalized Difference Infrared Index (NDII), Global Vegetation Moisture Index (GVMI) and Moisture Stress Index (MSI). Also, strong relationships were found between fuel moisture content (FMC) and VIs for the sites separately; however, they were weaker for the pooled data. The correlations between EWT/FMC and VIs were found to decrease progressively as the woody cover increased. Although these results suggest that NIR and SWIR reflectance can be used for the estimation of herbaceous water content, additional validation from an increased number of study sites is necessary to study the robustness of such indices for a larger variety of savanna vegetation types

Enabling private sector adaptation to climate change in sub-Saharan Africa

The private sector is increasingly recognised as having important potential to help society adapt and become more resilient to climate change. Yet there is limited research examining how to promote and facilitate private sector adaptation in developing countries and in particular how governments can create an enabling environment to stimulate and incentivise domestic private sector adaptation. In this paper, we address this gap through a review of the key factors required to provide an enabling environment for the private sector denoted by existing adaptation literatures. We do this with a focus on adaptation by small and medium enterprises (SMEs) in sub-Saharan Africa (SSA). To advance this review, we draw insights from a much larger, yet generally independent, literature on enabling environments for private sector development. This literature disaggregates the private sector and highlights key constraints to the development and growth of SMEs in SSA, including deficient infrastructure and evidence of an African gap in access to and use of finance. Both areas of scholarship are then combined in a framework identifying key ‘building blocks’ constituting enabling conditions for private sector adaptation. The framework could be applied in many ways including to focus strategies to enhance private sector adaptation and to identify trade-offs and interactions between policies or initiatives surrounding private sector development. By combining these literatures, we call for a more holistic approach to developing enabling environments for SME adaptation and climate resilient development, that addresses the broader structural deficits that condition vulnerability and barriers that limit adaptive capacity

Working Papers No. 291 and No. 258

The private sector plays a critical role in contributing to developing countries’ growth and development efforts and is increasingly recognised as a key actor in climate change resilience activities. This detailed paper addresses gaps in climate adaptation literature by reviewing factors required to provide an enabling environment for the private sector, with a focus on adaptation by small and medium enterprises (SMEs) in the semi-arid regions (SARs) of Kenya and Senegal. The identification of misalignments within existing regulatory frameworks and policies can lead to revisions and improvements in policy making. Greater targeting of support and training services will help SMEs implement adaptation measures.UKaid from the British peopl

Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications.

Globe-LFMC is an extensive global database of live fuel moisture content (LFMC) measured from 1,383 sampling sites in 11 countries: Argentina, Australia, China, France, Italy, Senegal, Spain, South Africa, Tunisia, United Kingdom and the United States of America. The database contains 161,717 individual records based on in situ destructive samples used to measure LFMC, representing the amount of water in plant leaves per unit of dry matter. The primary goal of the database is to calibrate and validate remote sensing algorithms used to predict LFMC. However, this database is also relevant for the calibration and validation of dynamic global vegetation models, eco-physiological models of plant water stress as well as understanding the physiological drivers of spatiotemporal variation in LFMC at local, regional and global scales. Globe-LFMC should be useful for studying LFMC trends in response to environmental change and LFMC influence on wildfire occurrence, wildfire behavior, and overall vegetation health

Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications

Globe-LFMC is an extensive global database of live fuel moisture content (LFMC) measured from 1,383 sampling sites in 11 countries: Argentina, Australia, China, France, Italy, Senegal, Spain, South Africa, Tunisia, United Kingdom and the United States of America. The database contains 161,717 individual records based on in situ destructive samples used to measure LFMC, representing the amount of water in plant leaves per unit of dry matter. The primary goal of the database is to calibrate and validate remote sensing algorithms used to predict LFMC. However, this database is also relevant for the calibration and validation of dynamic global vegetation models, eco-physiological models of plant water stress as well as understanding the physiological drivers of spatiotemporal variation in LFMC at local, regional and global scales. Globe-LFMC should be useful for studying LFMC trends in response to environmental change and LFMC influence on wildfire occurrence, wildfire behavior, and overall vegetation health