Land use and cover maps for Mato Grosso State in Brazil from 2001 to 2017
| Autor: | Pedro R. Andrade, Lorena A. Santos, Karine Reis Ferreira, Adeline Maciel, Rolf Simoes, Alber Sanchez, Alexandre Xavier Ywata de Carvalho, Michelle Cristina Araujo Picoli, Gilberto Camara |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Data Descriptor 010504 meteorology & atmospheric sciences Biome 0211 other engineering and technologies 02 engineering and technology Land cover Library and Information Sciences 01 natural sciences Education Environmental impact Agricultural productivity lcsh:Science 021101 geological & geomatics engineering 0105 earth and related environmental sciences Developing world Land use business.industry Amazon rainforest Environmental resource management Agriculture Forestry Computer Science Applications Environmental sciences Geography Satellite Image Time Series lcsh:Q Statistics Probability and Uncertainty business Relevant information Information Systems |
| Zdroj: | Scientific Data, Vol 7, Iss 1, Pp 1-10 (2020) Scientific Data |
| ISSN: | 2052-4463 |
| Popis: | This paper presents a dataset of yearly land use and land cover classification maps for Mato Grosso State, Brazil, from 2001 to 2017. Mato Grosso is one of the world’s fast moving agricultural frontiers. To ensure multi-year compatibility, the work uses MODIS sensor analysis-ready products and an innovative method that applies machine learning techniques to classify satellite image time series. The maps provide information about crop and pasture expansion over natural vegetation, as well as spatially explicit estimates of increases in agricultural productivity and trade-offs between crop and pasture expansion. Therefore, the dataset provides new and relevant information to understand the impact of environmental policies on the expansion of tropical agriculture in Brazil. Using such results, researchers can make informed assessments of the interplay between production and protection within Amazon, Cerrado, and Pantanal biomes. Measurement(s)land • land useTechnology Type(s)computational modeling techniqueFactor Type(s)year • geographic location • land use and cover classSample Characteristic - EnvironmentlandSample Characteristic - LocationMato Grosso State Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11440461 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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