Abstract:The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies) concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300-3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification) was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.

The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index (NDVI), hyperspectral characteristics (350-1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation (FAPAR), biomass, vegetation water content, and land-atmosphere exchanges of carbon (NEE) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE, with high values of ~-7.5 g C m(-2)  day(-1) during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata. This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350-1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models.

The main aim of this paper is to study land-atmosphere exchange of carbon dioxide (CO 2) for semi-arid savanna ecosystems of the Sahel region and its response to climatic and environmental change. A subsidiary aim is to study and quantify the seasonal dynamics in light use efficiency (e) being a key variable in scaling carbon fluxes from ground observations using earth observation data. The net ecosystem exchange of carbon dioxide (NEE) 2010-2013 was measured using the eddy covariance technique at a grazed semi-arid savanna site in Senegal, West Africa. Night-time NEE was not related to temperature, confirming that care should be taken before applying temperature response curves for hot dry semi-arid regions when partitioning NEE into gross primary productivity (GPP) and ecosystem respiration (R eco). Partitioning was instead done using light response curves. The values of e ranged between 0.02 g carbon (C) MJ À1 for the dry season and 2.27 g C MJ À1 for the peak of the rainy season, and its seasonal dynamics was governed by vegetation phenology, photosynthetically active radiation, soil moisture and vapor pressure deficit (VPD). The CO 2 exchange fluxes were very high in comparison to other semi-arid savanna sites; half-hourly GPP and R eco peaked at À43 mmol CO 2 m À2 s À1 and 20 mmol CO 2 m À2 s À1 , and daily GPP and R eco peaked at À15 g C m À2 and 12 g C m À2 , respectively. Possible explanations for the high CO 2 fluxes are a high fraction of C4 species, alleviated water stress conditions, and a strong grazing pressure that results in compensatory growth and fertilization effects. We also conclude that vegetation phenology, soil moisture, radiation, VPD and temperature were major components in determining the seasonal dynamics of CO 2 fluxes. Despite the height of the peak of the growing season CO 2 fluxes, the annual C budget (average NEE: À271 g C m À2) were similar to that in other semi-arid ecosystems because the short rainy season resulted in a short growing season. Global circulation models project a decrease in rainfall, an increase in temperature and a shorter growing season for the western Sahel region, and the productivity and the sink function of this semi-arid ecosystem may thus be lower in the future. 2015 Elsevier B.V. All rights reserved.

Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow-and fast-recovering changes in backscatter in close spatial and temporal proximity. In the study area in Madre de Dios, Peru, 2.3% of land was found to be disturbed over three years, with a false positive rate of 0.3% of area. A low, but significant, detection rate of degradation from sparse and small-scale selective logging was achieved. Disturbances were most common along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter, and backscatter decrease, suggested that large-scale deforestation was likely in areas with initially low biomass, either naturally or since already under anthropogenic use. Further, backscatter increases following disturbance suggested that radar can be used to characterize successional disturbance dynamics, such as biomass accumulation in lands post-abandonment. The presented radar-based detection algorithm is spatially and temporally scalable, and can support monitoring degradation and deforestation in tropical rainforests with the use of products from ALOS-2 and the future SAOCOM and BIOMASS missions.

The coexistence of trees and grasses is a defining feature of savannah ecosystems and landscapes. During recent decades, the combined effect of climate change and increased demographic pressure has led to complex vegetation changes in these ecosystems. A number of recent Earth observation (EO)-based studies reported positive changes in biological productivity in the Sahelian region in relation to increased precipitation, triggering an increased amount of herbaceous vegetation during the rainy season. However, this 'greening of the Sahel' may mask changes in the tree-grass composition, with a potential reduction in tree cover having important implications for the Sahelian population. Large-scale EO-based evaluation of changes in Sahelian tree cover is assessed by analysing long-term trends in dry season minimum normalized difference vegetation index (NDVI min) derived from three different satellite sensors: Système Pour l'Observation de la Terre (SPOT)-VEGETATION (VGT), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) dataset. To evaluate the reliability of using NDVI min as a proxy for tree cover in the Sahel, two factors that could potentially influence dry season NDVI min estimates were analysed: the total biomass accumulated during the preceding growing season and the percentage of burned area observed during the dry season. Time series of dry season NDVI min derived from low-resolution satellite time series were found to be uncorrelated to dry grass residues from the preceding growing season and to seasonal fire frequency and timing over most of the Sahel (88%), suggesting that NDVI min can serve as a proxy for assessing changes in tree cover. Good agreement (R 2 = 0.79) between significant NDVI min trends (p < 0.05) derived from VGT and MODIS was found. Significant positive trends in NDVI min were registered by both MODIS and VGT dry season NDVI min time series over the Western Sahel, whereas trends based on GIMMS data were negative for the greater part of the Sahel. EO-based trends were generally not confirmed at the local scale based on selected study cases, partly caused by a temporal mismatch between data sets (i.e. different periods of analysis). Analysis of desert area NDVI min trends indicates less stable values for VGT and GIMMS data as compared with MODIS. This suggests that trends in dry season NDVI min derived from VGT and GIMMS should be used with caution as an indicator for changes in tree cover, whereas the MODIS data stream shows a better potential for tree-cover change analysis in the Sahel.