Comparing parametric and non-parametric approaches for estimating trends in multi-year NDVI

The aim of this study is to systematically compare parametric and non-parametric techniques for analyzing trends in annual NDVI derived from NOAA AVHRR sensor in order to examine how trend type and departure from normality assumptions affect the accuracy of detecting long-term change. To generate annual data, the mean NDVI of a four-month long ‘green’ season was computed for fifteen sites (located in Africa, Spain, Italy, Sweden, and Iraq) from the GIMMS product for the periods 1982-2006. Trends in these time series were then estimated by Ordinary Least-Squares (OLS) regression (parametric) and the combined Mann-Kendall test with Theil-Sen slope estimator (non-parametric), and compared using slope value and statistical significance measures. We also estimated optimal polynomial model for the annual NDVI, by using Akaike Information Criterion (AIC), to determine the trend type at each site. Results indicate that slopes and their statistical significances obtained from the two approaches at sites with low degree polynomials (mostly linear) and steep monotonic (gradually increasing or decreasing) trends compare favourably with one another. At sites with weak linear slopes, the two approaches had similar results as well. Exceptions include sites with abrupt step-like changes resulting in departures from linearity and consequently high degree polynomials where the least-squares method outperformed the Mann-Kendall Theil-Sen method. In sum, we conclude that OLS is superior for detecting NDVI trends using annual data though further investigation using other techniques is recommended

The supply and demand of net primary production in the Sahel

Net primary production (NPP) is the principal source of energy for ecosystems and, by extension, human populations that depend on them. The relationship between the supply and demand of NPP is important for the assessment of socio-ecological vulnerability. We present an analysis of the supply and demand of NPP in the Sahel using NPP estimates from the MODIS sensor and agri-environmental data from FAOSTAT. This synergistic approach allows for a spatially explicit estimation of human impact on ecosystems. We estimated the annual amount of NPP required to derive food, fuel and feed between 2000 and 2010 for 22 countries in sub-Saharan Africa. When comparing annual estimates of supply and demand of NPP, we found that demand increased from 0.44 PgC to 1.13 PgC, representing 19% and 41%, respectively, of available supply due to a 31% increase in the human population between 2000 and 2010. The demand for NPP has been increasing at an annual rate of 2.2% but NPP supply was near-constant with an inter-annual variability of approximately 1.7%. Overall, there were statistically significant (p < 0.05) increases in the NPP of cropland (+6.0%), woodland (+6.1%) and grassland/savanna (+9.4%), and a decrease in the NPP of forests (−0.7%). On the demand side, the largest increase was for food (20.4%) followed by feed (16.7%) and fuel (5.5%). The supply-demand balance of NPP is a potentially important tool from the standpoint of sustainable development, and as an indicator of stresses on the environment stemming from increased consumption of biomass

The El Niño – La Niña cycle and recent trends in supply and demand of net primary productivity in African drylands

Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Climatic Change 138 (2016): 111-125, doi:10.1007/s10584-016-1730-1.Inter-annual climatic variability over a large portion of sub-Saharan Africa is under the influence of the El Niño-Southern Oscillation (ENSO). Extreme variability in climate is a threat to rural livelihoods in sub-Saharan Africa, yet the role of ENSO in the balance between supply and demand of net primary productivity (NPP) over this region is unclear. Here, we analyze the impact of ENSO on this balance in a spatially explicit framework using gridded population data from the WorldPop project, satellite-derived data on NPP supply, and statistical data from the United Nations. Our analyses demonstrate that between 2000 and 2013 fluctuations in the supply of NPP associated with moderate ENSO events average ±2.8 g C m-2 yr-1 across sub-Saharan drylands. The greatest sensitivity is in arid Southern Africa where a +1oC change in the Niño-3.4 sea surface temperature index is associated with a mean change in NPP supply of -6.6 g C m-2 yr-1. Concurrently, the population-driven trend in NPP demand averages 3.5 g C m-2 yr-1 over the entire region with densely populated urban areas exhibiting the highest mean demand for NPP. Our findings highlight the importance of accounting for the role ENSO plays in modulating the balance between supply and demand of NPP in sub-Saharan drylands. An important implication of these findings is that increase in NPP demand for socio-economic metabolism must be taken into account within the context of climate-modulated supplyFunding for this project was provided by the Swedish National Space Board (contract no. 100/11 to J.A.). A.M.A. received support from the Royal Physiographic Society in Lund and the Lund University Center for Studies of Carbon Cycle and Climate Interactions (LUCCI). C.C.U. was supported by NSF grant OCE-1203892.2017-07-0

Mapping Primary Production for the West African Sahel with Satellite Data

A light Use Efficiency (LUE) model is developed that allows the mapping of total growing season Gross Primary Production (GPP) for the West African Sahel, using the Normalized Difference Vegetation Index (NDVI) together with other data. Image quality may be poor in monthly NDVI maximum value composites as shown by an improved geostatistical noise estimation technique. Quality may be improved by other compositing methods that use NOAA AVHRR-derived surface temperature and scan angle information to reduce residual cloud amount and off-nadir bias. These data are then used in conjunction with ancillary information to map total growing season GPP using the LUE approach, which reduces the complexities of plant growth to a simple parametric statement. To overcome the lack of ground data, NOAA AVHRR-derived CLAVR (CLouds from AVHRR) fields are used to derive several key parameters of energy balance, including Photosynthetically Active Radiation (PAR). Fraction of absorbed Photosynthetically Active Radiation (FPAR) is calculated from the NDVI and multiplied with PAR to yield Absorbed Photosynthetically Active Radiation (APAR). A water stress scalar is estimated with a two-layer hydrological model that treats separately bare soil evaporation and transpiration. This scalar is used to reduce potential photosynthetic capacity in the LUE model, as defined by the product of APAR and the potential growth efficiency. The absolute precision of GPP estimates decreases for dense vegetation while the relative precision increases. LUE primary production estimates are systematically higher for dense vegetation when compared to point estimates from the CENTURY model. This bias is not apparent when compared to previous work reported in the literature. The LUE model may be used to address issues related to desertification, food security, and climate change

Meteorological, agricultural and socioeconomic drought in the Duhok Governorate, Iraqi Kurdistan

Drought is a recurrent natural hazard that is expected to increase in the future due to anthropogenic climate change. The Middle East region witnessed a drought period between 2007 and 2009 that has been reported to have severe consequences for the population, especially in Syria and Iraq. This study seeks to assess the spatial and temporal characteristics of the drought in the Duhok Governorate in Northern Iraq, focusing on meteorological, agricultural and socio-economic drought at province and village level. Satellite based precipitation data, validated by station data, were used in a meteorological drought assessment. To estimate the decreased precipitation’s effects on vegetation, an agricultural drought assessment was performed using Enhanced Vegetation Index (EVI) from multi-temporal satellite data. Vegetation anomalies were studied at provincial level, and also at village level where the anomalies were compared with survey data showing the socio-economic susceptibility to drought. The study confirms that precipitation dropped by approximately 50%, leading to a negative anomaly in vegetation conditions for 62% of Duhok Governorate’s area in 2008. Out of 50 assessed villages, 46 experienced a negative vegetation anomaly during the drought year, and three of those experienced a strong negative anomaly. Reports of drought as a problem were frequently recorded in the exposed villages, but was also related to the level of agricultural involvement. This study emphasizes the importance of understanding drought from both physical and socio-economic perspectives. Moreover, discrepancies in the datasets make a multi-source approach essential to avoid erroneous interpretations

A simple method to account for off-nadir scattering in the NOAA/NASA Pathfinder AVHRR Land Data Set

The radiometric distortion of reflected radiation received by the NOAA AVHRR sensor is brought on by the effects of viewing and solar illumination geometry, as well as atmospheric effects. This may lead to a gross underestimation of bioproductivity or crop yield from models which use high temporal resolution NOAA AVHRR data as an input. Accordingly, a simple angular correction method is presented using daily NDVI data over the Sudan from July, 1989 derived from the NOAA/NASA Pathfinder AVHRR Land Data Set. Its simplicity and expediency may render it suitable for operational monitoring programmes such as famine early warning

Rapid estimation of photosynthetically active radiation over the West African Sahel using the Pathfinder Land Data Set

Photosynthetically Active Radiation (PAR) is important for assessing both the impact of changing land cover on climate, and for modelling productivity on a regional scale, as well as its potential in areas that are vulnerable to food shortfalls. A relatively simple method that generates spatially comprehensive and representative values of PAR at time scales of 10-days (dekads) or longer is described, tested and implemented over a portion of West Africa. With simple equations to describe the geographical and temporal variation of global radiation receipt at the top of the atmosphere, daily cloud flags from the NOAA/NASA AVHRR Pathfinder Land Data Set (PAL) are used in conjunction with an empirical formula developed by Angstrom and constants tailored to West African conditions to estimate surface receipt of global radiation there. Ground observations of PAR from the HAPEX Sahel experiment (at 13°66' N and 2°53' E from 1992) are used to parameterise the relative sunshine duration variable in the Angstrom relation so as to minimise errors between observed and modelled PAR. Results indicate that PAR may be estimated to within 20 percent of observed values for 28 out of 36 10-day summation periods over a year. End-of-year accumulated PAR is estimated to within 1.96 percent. Normalised root mean square errors (NRMSEs) and normalised mean absolute errors (NMAEs) of 15.69 percent and 12.46 percent, respectively, were obtained for 10-day sums, with values of 10.96 percent and 8.74 percent, respectively, for monthly sums. The spatial variability of end-of-year PAR for 1992 is in accordance with what was expected. Though more accurate methods exist for achieving this, the technique is merited for its ease of application, using an accessible data set, over areas where solar irradiation measurements are lacking