Tobias Landmann

The Southern Africa Fire Network (SAFNet) regional burned-area product-validation protocol

The development of appropriate validation techniques is critical to assess uncertainties associated with satellite‐data‐based products, to identify needed product improvements and to allow products to be used appropriately. At regional to global scales, there are several outstanding issues in the development of robust validation methodologies, including the need to increase the quality and economy of product validation by developing and promoting international validation standards and protocols. This paper describes a protocol developed to validate a regional southern Africa burned‐area product derived from Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m time series data. The protocol is based upon interpretations by members of the Southern Africa Fire Network (SAFNet) of multitemporal Landsat Enhanced Thematic Mapper plus (ETM+) data to derive maps of the location and approximate date of burning. The validation data are derived using Landsat ETM+ scenes distributed to encompass representative regional variation in the conditions for which the MODIS burned‐area product was generated and to capture the more important factors that influence product performance. The protocol was developed by consensus to ensure inter‐comparison of the independent data derived by the different SAFNet members and to allow these data to be scaled up to provide regional validation of the MODIS burned‐area product. Biomass burning in southern Africa, the ETM+ sampling rationale, the interpretation and mapping approach, SAFNet member fire activities, and illustrative 2001 results and difficulties encountered with the protocol are described.

Characterizing the surface heterogeneity of fire effects using multi‐temporal reflective wavelength data

The relationship between changes observed in multi‐temporal remotely sensed data and disturbance processes are increasingly being studied in support of various land process modelling and management decision applications. The possibility of mapping both the location and degree of change and retrieving information concerning the disturbance process are primary goals. This paper studies changes in reflective wavelength data caused by the action of fire. We consider the heterogeneity of fire effects in terms of the fraction of the observation that burned (f) and the combustion completeness (cc). A spectral mixture model and field and satellite observations of prescribed fires are used to examine the relationship between change in reflectance, and cc and f. The prescribed fires were lit in different South African savannah types during the SAFARI 2000 dry season campaign. Implications for the development of methods to retrieve cc and f, and for the development of methods to map the spatial extent of fire‐affected areas with known detection capabilities are discussed.

Emissions of major gaseous and particulate species during experimental burns of southern African biomass

Received 2 June 2005; revised 31 October 2005; accepted 23 November 2005; published 22 February 2006. [1] Characteristic vegetation and biofuels in major ecosystems of southern Africa were sampled during summer and autumn 2000 and burned under semicontrolled conditions. Elemental compositions of fuels and ash and emissions of CO2, CO, CH3COOH, HCOOH, NOX ,N H3, HONO, HNO3, HCl, total volatile inorganic Cl and Br, SO2 and particulate C, N, and major ions were measured. Modified combustion efficiencies (MCEs, median = 0.94) were similar to those of ambient fires. Elemental emissions factors (EFel) for CH3COOH were inversely correlated with MCEs; EFels for heading and mixed grass fires were higher than those for backing fires of comparable MCEs. NOX ,N H3, HONO, and particulate N accounted for a median of 22% of emitted N; HNO3 emissions were insignificant. Grass fires with the highest EFels for NH3 corresponded to MCEs in the range of 0.93; grass fires with higher and low MCEs exhibited lower EFels. NH3 emissions for most fuels were poorly correlated with fuel N. Most Cl and Br in fuel was emitted during combustion (median for each = 73%). Inorganic gases and particulate ions accounted for medians of 53% and 30% of emitted Cl and Br, respectively. About half of volatile inorganic Cl was HCl indicating significant emissions of other gaseous inorganic Cl species. Most fuel S (median = 76%) was emitted during combustion; SO2 and particulate SO4� accounted for about half the flux. Mobilization of P by fire (median emission = 82%) implies large nutrient losses from burned regions and potentially important exogenous sources of fertilization for downwind ecosystems.

Wide Area Wetland Mapping in Semi-Arid Africa Using 250-Meter MODIS Metrics and Topographic Variables

Wetlands in West Africa are among the most vulnerable ecosystems to climate change. West African wetlands are often freshwater transfer mechanisms from wetter climate regions to dryer areas, providing an array of ecosystem services and functions. Often wetland-specific data in Africa is only available on a per country basis or as point data. Since wetlands are challenging to map, their accuracies are not well considered in global land cover products. In this paper we describe a methodology to map wetlands using well-corrected 250-meter MODIS time-series data for the year 2002 and over a 360,000 km2 large study area in western Burkina Faso and southern Mali (West Africa). A MODIS-based spectral index table is used to map basic wetland morphology classes. The index uses the wet season near infrared (NIR) metrics as a surrogate for flooding, as a function of the dry season chlorophyll activity metrics (as NDVI). Topographic features such as sinks and streamline areas were used to mask areas where wetlands can potentially occur, and minimize spectral confusion. 30-m Landsat trajectories from the same year, over two reference sites, were used for accuracy assessment, which considered the area-proportion of each class mapped in Landsat for every MODIS cell. We were able to map a total of five wetland categories. Aerial extend of all mapped wetlands (class “Wetland”) is 9,350 km2, corresponding to 4.3% of the total study area size. The classes “No wetland”/“Wetland” could be separated with very high certainty; the overall agreement (KHAT) was 84.2% (0.67) and 97.9% (0.59) for the two reference sites, respectively. The methodology described herein can be employed to render wide area base line information on wetland distributions in semi-arid West Africa, as a data-scarce region. The results can provide (spatially) interoperable information feeds for inter-zonal as well as local scale water assessments.

MODIS-based change vector analysis for assessing wetland dynamics in Southern Africa

The mapping and characterization of wetlands in semi-arid savannas is challenging due to the large interannual and seasonal flooding variability in these important and highly vulnerable ecosystems. This study shows the possibility of using 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) metrics (from 16 day composites) in change vector analysis (CVA) to map wetland dynamics in the Linyanti wetland (Namibia) between 2001 and 2010. For each pixel, we compute the interannual CVA intensity and the CVA direction, as well as the cumulative change intensity and the overall direction (trend) within the observation period. Both the change vector intensities and the corresponding change directions are necessary to interpret the interannual change and assess the 9 year trend. The interannual CVA intensities show a significant correlation with flooding magnitudes. The flooding magnitudes are derived from the Advanced Microwave Scanning Radiometer-Earth Observing System instrument (AMSR-E) radar observations for a hydrographic station located at the nearest inflow point into the Linyanti wetland. Given that long-term flooding records and satellite observations are available, the approach could be used to detect and interpret climate-induced inundation dynamics within wetlands in semi-arid Africa.

Occurrence of rift valley fever in cattle in Ijara district, Kenya

Ijara district in Kenya was one of the hotspots of rift valley fever (RVF) during the 2006/2007 outbreak which led to human and animal deaths causing huge economic and public health losses. The main constraint in the control and prevention of RVF is inadequate knowledge on its occurrence during the interepidemic period. This study was aimed at understanding the occurrence of RVF in cattle in Ijara to enable the development of improved community-based disease surveillance, prediction, control and prevention. Six herds each 700-1000 cattle were identified with participatory involvement of locals and project technical team of the project. One animal per herd was tagged with global position system (GPS) collar to enable follow up. Sero-surveys were conducted periodically to understand the herds movement through various ecological zones and risk of exposure to RVF virus. Sixty animals less than 3 years old from each herd were randomly selected each sampling time and sero-surveyed for RVF four times (September 2012, December 2012, February 2013 and May 2013) during the study period and along the nomadic movement route. The serum samples collected were subjected to RVF inhibition ELISA test to detect if there was exposure for RVF virus (RVFV). The RVF inhibition ELISA positive samples were subjected to IgM ELISA test to determine if the exposures were current or recent (within 14 days). The result of the survey indicated that 13.1% (183/1396) of cattle sero-surveyed had RVFV antibodies by inhibition ELISA test while 1.4% (18/1396) was positive for IgM ELISA test. The highest RVFV circulation was detected after herds pass through bony forest between Lamu and Ijara and Halei forested areas. These forested areas also had the highest IgM detections. The findings indicate that even limited rainfall was able to initiate RVFV circulation in Ijara region with highest circulation detected within forested areas with potential to become epidemic if rains persist with extensive flooding. There is need to carry out regular participatory disease surveillance in domestic animals and other host systems to identify risk locations in hotspot areas and carry out community awareness and focal vaccination campaigns against RVF for preparedness, prevention and control. Additionally, monitoring of environmental conditions in risky ecological zones to detect enhanced rainfall and flooding should be prioritized for preparedness.

Evaluating the sequential masking classification approach for improving crop discrimination in the Sudanian Savanna of West Africa

A variant of sequential masking classification is proposed for crop mapping.Individual crop types are classified using different image combinations.Accuracy of classifying individual crop classes improves by between 4% and 19%.Increased availability of satellite data can improve crop mapping in cloud-prone areas. Classification of remotely sensed data to reveal the spatial distribution of crop types has high potential for improving crop area estimates and supporting decision making. However, remotely sensed crop maps still demand improvements as e.g. variations in farm management practices (e.g. planting and harvesting dates), soil and other environmental factors cause overlaps in features available for classification and thus confusion in error matrices. In this study, a variant of the sequential masking classification technique was applied to multi-temporal optical and microwave remote sensing data (RapidEye, Landsat, TerraSAR-X) to improve the accuracy of crop discrimination in West Africa. This approach employs different sets of multi-temporal images to sequentially classify individual crop classes. The efficiency of the sequential masking approach was tested by comparing the results with that of a one-step classification, in which all crop classes were classified at the same time. Compared to the one-step classification, the sequential masking approach improved overall classification accuracies by between 6% and 9% while increments in the accuracy of individual crop classes were between 4% and 19%. The McNemars statistical test showed that the observed differences in accuracy of the two approaches were statistically significant at the 1% significance level. The findings of this study are important for crop mapping efforts in West Africa, where data and methodological constraints often hinder the accurate discrimination of crops.

Remote sensing of vegetation fires and its contribution to a fire management information system

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then precedes a description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate the practical use of remotely sensed fire information.

The utility of satellite fire product accuracy Information-perspectives and recommendations from the Southern Africa fire network

This correspondence gives Southern Africa Fire Network (SAFNet) perspectives on the utility of satellite fire product accuracy information, drawing on two main sources: insights gained during SAFNets six years of working together, and relevant findings from a SAFNet focus group study that explored factors that promote and constrain the use of the MODIS fire products. In giving this perspective, we comment on the approach and findings of recent fire product validation articles, including the two contained in this special issue. We recommend five ways that validation activities might be made more relevant to users and better connect producers of remotely sensed products to users in order to communicate satellite fire product accuracy information more effectively

Dynamics of MODIS Time Series for Ecological Applications in Southern Africa

Intra and inter-annual vegetation dynamics indicate important ecological processes. The first are the basis of phenological analysis and describe the vegetation state and seasonal development. Inter-annual observations can be used to monitor multi-year modification and conversion processes of the land surface. Time series of remotely sensed parameters are important to understand these annual and inter-annual vegetation dynamics. Remotely sensed parameters such as vegetation indices, describing the activity of chlorophyll active vegetation, are available on a daily basis. This study employs annual time series of the Enhanced Vegetation Index (EVI) of the MODIS instrument for South Africa. Four phenologically described vegetation types are distinguished, including non-modal, uni-modal with maximum in summer or winter and bimodal cycles. Temporal cross-correlation is used to analyze phenological shifts of the EVI for consecutive years. Furthermore, EVI time series are related to high spatial resolution precipitation rate estimates. Considerable shifts in EVI phenology are shown for the northern continental provinces Limpopo, North West Province, and northern Mpumalanga and partly for Kwazulu Natal on the eastern coast. These phenological shifts in time are spatially related to high biomass land cover units such as forested land. Notably small shifts are identified for winter rain environments in the Cape floristic region indicating a higher stability of the vegetation development. A near constant temporal lag of one to two months between precipitation and EVI for six years indicates the functionality of the natural ecosystems in South Africa and the dependence on rain onset for vegetation green-up.