In northern Brazilian Amazon, the crops, savannahs and rainforests form a complex landscape where land use and land cover (LULC) mapping is difficult. Here, data from the Operational Land Imager (OLI)/Landsat-8 and Phased Array type L-band Synthetic Aperture Radar (PALSAR-2)/ALOS-2 were combined for mapping 17 LULC classes using Random Forest (RF) during the dry season. The potential thematic accuracy of each dataset was assessed and compared with results of the hybrid classification from both datasets. The results showed that the combination of PALSAR-2 HH/HV amplitudes with the reflectance of the six OLI bands produced an overall accuracy of 83% and a Kappa of 0.81, which represented an improvement of 6% in relation to the RF classification derived solely from OLI data. The RF models using OLI multispectral metrics performed better than RF models using PALSAR-2 L-band dual polarization attributes. However, the major contribution of PALSAR-2 in the savannahs was to discriminate low biomass classes such as savannah grassland and wooded savannah.
The unpredictable Anthropocene poses the challenge of imagining a radically different, equitable and sustainable world. Looking 100 years ahead is not easy, and especially as millennials, it appears quite bleak. This paper is the outcome of a visioning exercise carried out in a 2-day workshop, attended by 33 young early career professionals under the auspices of IPBES. The process used Nature Futures Framework in an adapted visioning method from the Seeds of Good Anthropocene project. Four groups envisioned more desirable future worlds; where humanity has organised itself, the economy, politics and technology, to achieve improved nature-human well-being. The four visions had differing conceptualisations of this future. However, there were interesting commonalities in their leverage points for transformative change, including an emphasis on community, fundamentally different economic systems based on sharing and technological solutions to foster sustainability and human-nature connectedness. Debates included questioning the possibility of maintaining local biocultural diversity with increased connectivity globally and the prominence of technology for sustainability outcomes. These visions are the first step towards a wider galvanisation of youth visions for a brighter future, which is often missing in the arena where it can be taken seriously, to trigger more transformative pathways towards meeting global goals ARTICLE HISTORY
Over the past few decades, a significant amount of agricultural land has been lost due to soil degradation/desertification. In addition, the increasing frequency of extreme events, such as intense droughts and forest fires, has negatively impacted various ecosystem services. Two of the main Brazilian biomes—the Cerrado and the Caatinga—have been affected by increased rainfall variability, leading to desertification, increased fire frequency, and, consequently, rising concerns regarding the water and food security of the local population. In this study, we develop a methodology to assess these impacts using a Socio-Environmental Vulnerability Index (SEVI) that combines physical, environmental, and socio-economic indicators related to exposure, sensitivity, and adaptation, as well as including socio-environmental feedback. The developed SEVI is then applied to the São Francisco and Parnaíba river basins. The proposed index is based on the MEDALUS methodology and is adapted to include multiple biological, physical, and socio-economic indicators, allowing for the discrimination of areas characterized by different levels of vulnerability. We also analyze the effectiveness of governmental policies, such as the creation of conservation areas and the rural registration of properties, in reducing vulnerability. The SEVI analysis highlights that adaptive capacity is the main constraint for reducing socio-environmental vulnerability in the Parnaíba basin, while exposure and sensitivity are the greater challenges in the São Francisco basin. The results of this study are crucial for the prioritization of recovery actions in degraded areas.
Agricultural expansion and intensification enabled growth of food production but resulted in serious environmental changes. In light of that, debates concerning sustainability in agriculture arises on scientific literature. Land sharing and land sparing are two opposite models for framing agricultural sustainability. The first aims to integrate agricultural activities with biodiversity conservation by means of enhancing the quality of the agricultural matrix in the landscape towards a wildlife friendly matrix. The other model aims to spare natural habitats from agriculture for conservation. This work aimed to explore spatial evidences of land sharing/sparing and its relationship with rural population in the Brazilian Cerrado. A Land Sharing/Sparing Index based on TerraClass Cerrado map was proposed. Spatial analysis based on Global and Local Moran statistics and Geographically Weighted Regression were made in order to explore the influence of local rural population on the probability of spatial land sharing/sparing clusters occurrence. Spatial patterns of land sharing were found in the Cerrado and a positive association with rural population was found in some regions, such as in its northern portion. Land use policies should consider regional infrastructural and participative governance potentialities. The results suggests possible areas where joint agricultural activities and human presence may be favourable for biodiversity conservation.
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