ISSN: 2157-7617

Jornal de Ciências da Terra e Mudanças Climáticas

Acesso livre

Nosso grupo organiza mais de 3.000 Séries de conferências Eventos todos os anos nos EUA, Europa e outros países. Ásia com o apoio de mais 1.000 Sociedades e publica mais de 700 Acesso aberto Periódicos que contém mais de 50.000 personalidades eminentes, cientistas de renome como membros do conselho editorial.

Periódicos de acesso aberto ganhando mais leitores e citações
700 periódicos e 15 milhões de leitores Cada periódico está obtendo mais de 25.000 leitores

Indexado em
  • Índice de Fonte CAS (CASSI)
  • Índice Copérnico
  • Google Scholar
  • Sherpa Romeu
  • Acesso Online à Pesquisa no Meio Ambiente (OARE)
  • Abra o portão J
  • Genâmica JournalSeek
  • JornalTOCs
  • Diretório de Periódicos de Ulrich
  • Acesso à Pesquisa Online Global em Agricultura (AGORA)
  • Centro Internacional de Agricultura e Biociências (CABI)
  • RefSeek
  • Universidade Hamdard
  • EBSCO AZ
  • OCLC – WorldCat
  • Convocação de Proquest
  • Catálogo online SWB
  • Publons
  • Euro Pub
  • ICMJE
Compartilhe esta página

Abstrato

Linking Spatialized Indicators of Desertification Risks with Observed Land Use/Land Cover Change: An Operational Monitoring System of Desertification

Fetoui M, Loireau M, Essifi B, Chouikhi F, Tarhouni M, Sghaier M, Laques AE and Dérioz P

The need of useful information for decision-makers to fight against desertification in Tunisian dry zones leads to conceive assessing and monitoring systems that can supply synthetic indicators. These latter should integrate socioeconomic and environmental dimensions with their spatial and temporal diversity at the local scale. This paper proposes an example of information system entitled SIELO (information system for operational desertification monitoring at the local scale). This system attempts to create the link between i) spatialized indicators of desertification risks, built in connection with the systematic complexity of desertification and ii) observed Land Use/ Land Cover (LU/LC) Change. The first type of data arises from pre-existing environmental model: LEIS model (Local Environmental Information System). The second type of data is extracted from satellite images acquired according to regular time steps. The proposed approach is based also on the spatializing of knowledge, via the ‘‘landscape’’ tool in particular. We illustrate the feasibility and the operational effectiveness of a developed software prototype (SIELO v1.0) with an initial application in a Tunisian dry zone. This system showed that it has the capacity to feed an operational monitoring of desertification according to the state of LU/LC directly observed or measured in several dates. Then, it can be useful for the decision-makers in their programs of fighting against desertification, but also to manage uncertainties in southeastern Tunisia, especially climate variability and climate change.