Else Swinnen

Crop mapping in countries with small-scale farming: a case study for West Shewa, Ethiopia

Remote sensing is nowadays considered to be a valuable input for the annual collection of crop statistics. Derived crop maps can serve as a baseline for yield or area estimation or to target next years census. For subsistence farming, where small parcels are mixed with other land use, crop mapping remains very challenging. This article evaluates the potential of discriminating crops in West Shewa, an area with small-scale farming in central Ethiopia. A hard classification of high-resolution (30 m) images, yielding good results for commercial farming, could not deal with mixed pixels due to the small parcels. Very high resolution (4 m) images have a more appropriate pixel size, although they only cover subsets of the region. The very high resolution classification was used to calibrate a neural network for sub-pixel classification of the high resolution images. The accuracies were not satisfactory, but did at least demonstrate the potential of this approach.

Vegetation response to precipitation variability in East Africa controlled by biogeographical factors

Ecosystem sensitivity to climate variability varies across East Africa, and identifying the determinant factors of this sensitivity is crucial to assessing region-wide vulnerability to climate change and variability. Such assessment critically relies on spatiotemporal datasets with inherent uncertainty, on new processing techniques to extract interannual variability at a priori unknown time scales and on adequate statistical models to test for biogeographical effects on vegetation-precipitation relationships. In this study, interannual variability in long term records of Normalized Difference Vegetation Index (NDVI) and satellite-based precipitation estimates was detected using Ensemble Empirical Mode Decomposition (EEMD) and Standardized Precipitation Index (SPI) with varying accumulation periods. Environmental effect modeling using additive models with spatially correlated effects showed that ecosystem sensitivity is primarily predicted by biogeographical factors such as annual precipitation distribution (reaching maximum sensitivity at 500 mm yr-1), vegetation type and structure, ocean-climate coupling and elevation. The threat of increasing climate variability and extremes impacting productivity and stability of ecosystems is most imminent in semi-arid grassland and mixed cropland ecosystems. The influence of oceanic phenomena such as El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) is foremost reflected in precipitation variability, but prolonged episodes also pose risks for long-term degradation of tree-rich ecosystems in the East African Great Lakes region.

Ten-daily global composites of METOP-AVHRR

Systematic scanning of the earth surface could be achieved for the first time in 1978, with the launch of the earth observation system NOAA-AVHRR. Some twenty years later, the SPOT-VEGETATION instrument introduced significant improvements at the levels of image quality, timeliness and availability. Since the start in April 1998, VITO is responsible for the central processing, archiving and distribution of the VEGETATION data. This paper briefly announces how a similar service is being established at VITO to provide the same kind of image data from the recently launched METOP-AVHRR.

Sub-pixel land-cover classification with SPOT-VEGETATION imagery

Knowledge about global land cover is an important input for the modelling of ecological and environmental processes. Production of such global vegetation maps can be facilitated by using automated methods for classification. Two neural network strategies, an overall and class-specific network(s), were tested on a part of Europe. This study indicates that sub-pixel proportion estimates can be assessed quite accurately from 1-km resolution SPOT-VEGETATION imagery.

Assessment of the impact of the orbital drift of SPOT-VGT1 by comparison with SPOT-VGT2 data

The Système Pour l’Observation de la Terre 5 – VEGETATION 2 (SPOT 5 – VGT2) instrument started to drift in orbit from early 2011, but currently the overpass time is still within mission requirements (less than 20 min deviation from 10:30 local equator crossing time). To determine the operational lifetime of the VGT2 instrument, it was necessary to investigate the impact of orbital drift beyond these mission requirements such that the VGT time series remains consistent over time. To this purpose, the impact of orbital drift on reflectance values and on the normalized difference vegetation index (NDVI) from the VGT1 instrument (onboard SPOT 4) in the period May 2009 to April 2012 was investigated using paired observations from VGT1 and VGT2. The comparison is thus a relative one, which has the advantage that land-cover change or trends in land-cover change are not interfering with the analysis. VGT2 acted as the reference against which the VGT1 data were compared. First, the magnitude of the solar zenith angle (SZA) change in the overlapping time period was investigated. This SZA change is largest near the equator and decreases considerably with increasing latitude. The overpass difference of VGT1 and VGT2 of 37 min resulted in maximum SZA changes of 9°, which is still well within the SZA variability of standard VGT products (i.e. 20°). Second, for a number of selected sites of 1° × 1° size with one dominant land cover, we investigated in detail the time evolution of some measures of agreement and disagreement. In the third analysis, systematic subsamples of the global images were used. From these images, the relative difference between VGT1 and VGT2 – with VGT2 as reference – was assessed as a function of the SZA of VGT2 and for different ranges of SZA difference. An increase of 10–20% in the relative difference between VGT1 and VGT2 was observed for the four spectral bands. The impact on the NDVI was negligible. Based on the obtained results, an alternative compositing approach is formulated in order to maintain the quality of the VGT standard products with a similar orbital drift as investigated in this study.

Monitoring environmental health using SPOT-VEGETATION-derived and field-measured spectral indices in Karabash, Russia

The objective of this study was to use satellite imagery combined with field-based spectral analysis to assess the impacts of mining-related activities on vegetation around the smelter town of Karabash, South Ural Mountains of Russia. Time series analysis of normalized difference vegetation index (NDVI) and fraction of absorbed photosynthetically active radiation (FAPAR) images derived from Système Pour l’Observation de la Terre (SPOT)-VEGETATION was combined with the analysis of vegetation stress indices calculated from 140 in situ spectral measurements. Correlation analyses have revealed that vegetation stress affects vegetation density and resilience, and that it impedes a gradual increase in photosynthetic activity in the most affected areas ranging up to 10 km from the smelter. The prolongation of the growing season of healthier vegetation at greater distances, showing higher vegetation density, lower variation, and a more positive trend over time, can possibly be related to climate change. Although land cover shows a concentric pattern around Karabash, the analysis revealed that both spectral and time series-derived indices are defined more by the distance to the Karabash smelter and vegetation stress, rather than by the land cover class.

Joint retrieval of surface reflectance and aerosol properties from PROBA-V observations, part I: Algorithm performance evaluation

CISAR, a novel and versatile algorithm for the joint retrieval of surface reflectance and aerosol properties, has been applied on PROBA-V observations from years 2014–2015 in the framework of the Advanced Land, Aerosol and Coastal products for PROBA-V (PV-LAC) ESA project. This algorithm allows a continuous variation of the surface and atmospheric state variables in the solution space as it solves the solution of the radiative transfer equation online. The inversion is performed with an Optimal Estimation (OE) approach, which finds the best balance between the information that can be derived from the observations and the prior information. Retrieval uncertainties are also estimated from the OE theory and these account for both observation and prior information uncertainties. The role of temporal information in regulating possible surface and aerosol variations is analysed in this paper against simulated PROBA-V observations.

Evaluation of PROBA-V Collection 1: Refined Radiometry, Geometry, and Cloud Screening

PROBA-V (PRoject for On-Board Autonomy–Vegetation) was launched in May-2013 as an operational continuation to the vegetation (VGT) instruments on-board the Système Pour l’Observation de la Terre (SPOT)-4 and -5 satellites. The first reprocessing campaign of the PROBA-V archive from Collection 0 (C0) to Collection 1 (C1) aims at harmonizing the time series, thanks to improved radiometric and geometric calibration and cloud detection. The evaluation of PROBA-V C1 focuses on (i) qualitative and quantitative assessment of the new cloud detection scheme; (ii) quantification of the effect of the reprocessing by comparing C1 to C0; and (iii) evaluation of the spatio-temporal stability of the combined SPOT/VGT and PROBA-V archive through comparison to METOP/advanced very high resolution radiometer (AVHRR). The PROBA-V C1 cloud detection algorithm yields an overall accuracy of 89.0%. Clouds are detected with very few omission errors, but there is an overdetection of clouds over bright surfaces. Stepwise updates to the visible and near infrared (VNIR) absolute calibration in C0 and the application of degradation models to the SWIR calibration in C1 result in sudden changes between C0 and C1 Blue, Red, and NIR TOC reflectance in the first year, and more gradual differences for short-wave infrared (SWIR). Other changes result in some bias between C0 and C1, although the root mean squared difference (RMSD) remains well below 1% for top-of-canopy (TOC) reflectance and below 0.02 for the normalized difference vegetation index (NDVI). Comparison to METOP/AVHRR shows that the recent reprocessing campaigns on SPOT/VGT and PROBA-V have resulted in a more stable combined time series.

Proba-V cloud detection Round Robin: Validation results and recommendations

This paper discusses results from 12 months of a Round Robin exercise aimed at the inter-comparison of different cloud detection algorithms for Proba-V. Clouds detection is a critical issue for satellite optical remote sensing, since potential errors in cloud masking directly translates into significant uncertainty in the retrieved downstream geophysical products. Cloud detection is particularly challenging for Proba-V due to the presence of a limited number of spectral bands and the lack of thermal infrared bands. The main objective of the project was the inter-comparison of several cloud detection algorithms for Proba-V over a wide range of surface types and environmental conditions. Proba-V Level 2a products have been distributed to six different algorithm providers representing companies and research institutes in several European countries. The considered cloud detection approaches are based on different strategies: Neural Network, Discriminant Analysis, Multi-spectral and Multi-textural Thresholding, Self-Organizing Feature Maps, Dynamic Thresholding, and physically-based retrieval of Cloud Optical Thickness. The results from all algorithms were analysed and compared against a reference dataset, consisting of a large number (more than fifty thousands) of visually classified pixels. The quality assessment was performed according to a uniform methodology and the results provide clear indication on the potential best-suited approach for next Proba-V cloud detection algorithm.

Angular normalisation of PROBA-V 300m NDVI

This contribution describes an ongoing effort, within the framework of the Copernicus Global Land Service 1, to develop an updated PROBA-V 300m NDVI product. Unlike previous versions of the PROBA-V NDVI at 300m, a normalisation for viewing and illumination geometry is performed and its temporal compositing strategy is aimed to maintain near real-timeness as possible. We use the MSG/SEVIRI NDVI angular normalised time series with high temporal resolution (daily cadence) to evaluate the near real-timeness of the PROBA-V NDVI 300m compositing strategy. Since PROBA-V does not have on-board propellant, the overpass times are expected to gradually differ from the at-launch value. Therefore, an angular normalised PROBA-V NDVI 300m product becomes pivotal to ensure continuity with the Sentinel 3 missions.