Woody vegetation cover monitoring with multi-temporal Landsat data and Random Forests: the case of the Northwest Province (South Africa)

Land degradation and desertification (LDD) are serious global threats to humans and the environment. Globally, 10-20% of drylands and 24% of the world’s productive lands are potentially degraded, which affects 1.5 billion people and reduces GDP by €3.4 billion. In Africa, LDD processes affect up to a third of savannahs, leading to a decline in the ecosystem services provided to some of the continent’s poorest and most vulnerable communities. Indirectly, LDD can be monitored using relevant indicators. The encroachment of woody plants into grasslands, and the subsequent conversion of savannahs and open woodlands into shrublands, has attracted a lot of attention over the last decades and has been identified as an indicator of LDD. According to some assessments, bush encroachment has rendered 1.1 million ha of South African savanna unusable, threatens another 27 million ha (~17% of the country), and has reduced the grazing capacity throughout the region by up to 50%. Mapping woody cover encroachment over large areas can only be effectively achieved using remote sensing data and techniques. The longest continuously operating Earth-observation program, the Landsat series, is now freely-available as an atmospherically corrected, cloud masked surface reflectance product. The availability and length of the Landsat archive is thus an unparalleled Earth-observation resource, particularly for long-term change detection and monitoring. Here, we map and monitor woody vegetation cover in the Northwest Province of South Africa, a mosaic of 12 Landsat scenes that expands over more than 100,000km2. We employ a multi-temporal approach with dry-season TM, ETM+ and OLI data from 15 epochs between 1989 to 2015. We use 0.5m-pixel colour aerial photography to collect >15,000 samples for training and validating a Random Forest model to map woody cover, grasses, crops, urban and bare areas. High classification accuracies are achieved, especially so for the two cover types indirectly linked with bush encroachment, i.e. woody cover and grasses. Results show that there is a steady increase in woody vegetation cover over the 26-year-long period of study in the expense of graminoids. We identify woody vegetation encroachment ‘hot-spots’ where mitigation measures are required and thus provide a management tool for the prioritisation of such measures in degraded and food-insecure areas. Our approach can be instrumental in informing international land degradation mitigation and adaptation policy interventions that can advance sustainable development and protect livelihoods and lives in South Africa and other African savannahs

Landsat-based woody vegetation cover monitoring in Southern African savannahs

Mapping woody cover over large areas can only be effectively achieved using remote sensing data and techniques. The longest continuously operating Earth-observation program, the Landsat series, is now freely-available as an atmospherically corrected, cloud masked surface reflectance product. The availability and length of the Landsat archive is thus an unparalleled Earth-observation resource, particularly for long-term change detection and monitoring. Here, we map and monitor woody vegetation cover in the Northwest Province of South Africa, an area of more than 100,000km2 covered by 11 Landsat scenes. We employ a multi-temporal approach with dry-season data from 7 epochs between 1990 to 2015. We use 0.5m-pixel colour aerial photography to collect >15,000 point samples for training and validating Random Forest classifications of (i) woody vegetation cover, (ii) other vegetation types (including grasses and agricultural land), and (iii) non-vegetated areas (i.e. urban areas and bare land). Overall accuracies for all years are around 80% and overall kappa between 0.45 and 0.66. Woody vegetation covers a quarter of the Province and is the most accurately mapped class (balanced accuracies between 0.74-0.84 for the 7 epochs). There is a steady increase in woody vegetation cover over the 25-year-long period of study in the expense of the other vegetation types. We identify potential woody vegetation encroachment 'hot-spots' where mitigation measures might be required and thus provide a management tool for the prioritisation of such measures in degraded and food-insecure areas

Optimisation of regional scale woody vegetation cover mapping with optical, thermal and radar data

Woody perennial vegetation is an integral part of savannah ecosystems and plays an important role in carbon cycling and ecosystem service provision. Accurately mapping its presence and its characteristics can provide useful input to global carbon emissions models as well regional policy decision making efforts regarding bush control or the overexploitation of fuelwood. Recent attempts to map the extent of savannah woody cover over the regional scale have employed Earth observation data either from optical or radar sensors, and most commonly from the dry season when the spectral difference from the ‘background’ grasses is maximised. By far the most common practice has been the use of Landsat optical bands, but some studies have also used vegetation indices or L-band or C-band SAR data. However, conflicting reports with regards to the effectiveness of the different approaches have emerged leaving the respective land cover mapping community with unclear methodological pathways to follow. We address this issue by employing Landsat and ALOS PALSAR data, together with colour aerial photography for training and validation of random forest regressions, to assess the accuracy of mapping woody vegetation when: (a) data from either or both seasons are considered; (b) annual PALSAR mosaics or the actual PALSAR data are used on their own or together with the optical data; (c) vegetation indices are calculated and are used either on their own or together with the Landsat bands; and (iv) thermal infrared information is not discarded but included in the parameterisation. We test our approach in an area of the Northwest Province of South Africa which spans over 6 Landsat scenes, covering an area of approximately 53,000 km2. Our hard classification results (woody vegetation, non-woody vegetation and no-vegetation) show that the most accurate estimates are produced from the model that incorporates all 23 parameters: Landsat optical and thermal bands and three vegetation indices (NDVI, MSAVI and TNDVI) and HH polarised PALSAR data for the dry and wet seasons (overall accuracy: 89%; woody cover balanced accuracy: 91%, producer’s accuracy: 83% and user’s accuracy: 90%). The combination of either dry season Landsat bands with the HV polarised radar data, appears to be sufficient for achieving woody cover balanced accuracies of 89%. Dry season optical bands alone are able to map woody cover with more than 81% balanced accuracy and the accuracy increases by the inclusion of either the vegetation indices or the TIR band (to 83% and 84%, respectively). Our findings can provide much needed assistance to woody vegetation monitoring efforts in southern African savannahs where the process is partly related with bush encroachment and land degradation brought about by recent climatic changes and overgrazing

Savannah fractional woody vegetation cover mapping with optical and radar data and machine learning

The fraction of woody vegetation plays an important role in natural and anthropogenic processes of savannah ecosystems. We investigate the optimal combination of Landsat optical and thermal bands as well as ALOS PALSAR L-band radar data from both wet and dry seasons for the mapping of fractional woody vegetation cover in southern African savannah environments. We employ colour aerial photography for sampling and validation and a random forest classification approach to map the fraction of woody cover in the Northwest Province of South Africa. Our results from random forests classifications show that the most accurate estimates are produced from the model that incorporates all parameters: Landsat optical and thermal bands and vegetation indices for the dry and wet seasons, and HH and HV polarised ALOS PALSAR L-band data. However, the combination of the six Landsat bands from either the wet or the dry season with either the HH or the HV PALSAR band, appears to be sufficient for achieving fractional woody cover balanced accuracies of >85%. Dry season optical bands alone are able to map fractional woody cover with more than 80% balanced accuracy. Our findings can provide much needed assistance to woody vegetation monitoring efforts in southern African savannahs where its expansion over the last decades is partly attributed to bush encroachment and land degradation brought about by recent climatic changes and/or land mismanagement

Lifetime and past-year prevalence of children’s exposure to violence in 9 Balkan countries: the BECAN study

Background Children’s exposure to violence is a major public health issue. The Balkan epidemiological study on Child Abuse and Neglect project aimed to collect internationally comparable data on violence exposures in childhood. Methods A three stage stratified random sample of 42,194 school-attending children (response rate: 66.7%) in three grades (aged 11, 13 and 16 years) was drawn from schools in Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Former Yugoslavian Republic of Macedonia (FYROM), Greece, Romania, Serbia and Turkey. Children completed the ICAST-C questionnaire, which measures children’s exposure to violence by any perpetrator. Results Exposure rates for psychological violence were between 64.6% (FYROM) and 83.2% (Greece) for lifetime and 59.62% (Serbia) and 70.0% (Greece) for past-year prevalence. Physical violence exposure varied between 50.6% (FYROM) and 76.3% (Greece) for lifetime and 42.5% (FYROM) and 51.0% (Bosnia) for past-year prevalence. Sexual violence figures were highest for lifetime prevalence in Bosnia (18.6%) and lowest in FYROM (7.6%). Lifetime contact sexual violence was highest in Bosnia (9.8%) and lowest in Romania (3.6%). Past-year sexual violence and contact sexual violence prevalence was lowest in Romania (5.0 and 2.1%) and highest in Bosnia (13.6 and 7.7% respectively). Self-reported neglect was highest for both past-year and lifetime prevalence in Bosnia (48.0 and 20.3%) and lowest in Romania (22.6 and 16.7%). Experiences of positive parental practices were reported by most participating children in all countries. Conclusions Where significant differences in violence exposure by sex were observed, males reported higher exposure to past-year and lifetime sexual violence and females higher exposure to neglect. Children in Balkan countries experience a high burden of violence victimization and national-level programming and child protection policy making is urgently needed to address this