scholarly journals Land use and cover change dynamics in Zambia's Solwezi copper mining district

2021 ◽  
pp. e01007
Author(s):  
Xavier T. Tiamgne ◽  
Felix K. Kalaba ◽  
Vincent R. Nyirenda
Keyword(s):  
Land Use ◽  
Copper Mining ◽  
Mining District ◽  
Change Dynamics ◽  
Land Use And Cover

Impacts of land use and cover type on runoff and soil erosion in a marginal area of Portugal

2011 ◽  
Vol 31 (2) ◽  
pp. 687-699 ◽  
Author(s):  
Adélia N. Nunes ◽  
António C. de Almeida ◽  
Celeste O.A. Coelho
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Cover Type ◽  
Land Use And Cover

scholarly journals Identifying Spatiotemporal Patterns in Land Use and Cover Samples from Satellite Image Time Series

2021 ◽  
Vol 13 (5) ◽  
pp. 974
Author(s):  
Lorena Alves Santos ◽  
Karine Ferreira ◽  
Michelle Picoli ◽  
Gilberto Camara ◽  
Raul Zurita-Milla ◽  
...  
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
Time Series ◽  
Satellite Image ◽  
Spatiotemporal Patterns ◽  
Supervised Machine Learning ◽  
Learning Methods ◽  
Self Organizing Maps ◽  
Machine Learning Methods ◽  
Land Use And Cover

The use of satellite image time series analysis and machine learning methods brings new opportunities and challenges for land use and cover changes (LUCC) mapping over large areas. One of these challenges is the need for samples that properly represent the high variability of land used and cover classes over large areas to train supervised machine learning methods and to produce accurate LUCC maps. This paper addresses this challenge and presents a method to identify spatiotemporal patterns in land use and cover samples to infer subclasses through the phenological and spectral information provided by satellite image time series. The proposed method uses self-organizing maps (SOMs) to reduce the data dimensionality creating primary clusters. From these primary clusters, it uses hierarchical clustering to create subclusters that recognize intra-class variability intrinsic to different regions and periods, mainly in large areas and multiple years. To show how the method works, we use MODIS image time series associated to samples of cropland and pasture classes over the Cerrado biome in Brazil. The results prove that the proposed method is suitable for identifying spatiotemporal patterns in land use and cover samples that can be used to infer subclasses, mainly for crop-types.

High concentrations of metals in the waters from Araguari River lower section (Amazon biome): Relationship with land use and cover, ecotoxicological effects and risks to aquatic biota

Chemosphere ◽  
2021 ◽  
pp. 131451
Author(s):  
Lucilene Finoto Viana ◽  
Fábio Kummrow ◽  
Claudia Andrea Lima Cardoso ◽  
Nathalya Alice de Lima ◽  
Júlio César Jut Solórzano ◽  
...  
Keyword(s):  
Land Use ◽  
Aquatic Biota ◽  
Lower Section ◽  
Ecotoxicological Effects ◽  
High Concentrations ◽  
Land Use And Cover

Temporal Geochemical Evolution of Neogene Magmatism in the Baguio Gold?Copper Mining District (Northern Luzon, Philippines)

2007 ◽  
Vol 57 (2) ◽  
pp. 197-218 ◽  
Author(s):  
Mireille Polve ◽  
Rene C. Maury ◽  
Sebastien Jego ◽  
Herve Bellon ◽  
Ahmed Margoum ◽  
...  
Keyword(s):  
Geochemical Evolution ◽  
Copper Mining ◽  
Mining District

Anomalous Trace Element Composition of Coastal Sediments near the Copper Mining District of Santa Rosalía, Peninsula of Baja California, Mexico

2000 ◽  
Vol 65 (2) ◽  
pp. 261-268 ◽  
Author(s):  
E. N. Shumilin ◽  
G. Rodríguez-Figueroa ◽  
O. Morton Bermea ◽  
E. Lounejeva Baturina ◽  
E. Hernández ◽  
...  
Keyword(s):  
Trace Element ◽  
Baja California ◽  
Trace Element Composition ◽  
Element Composition ◽  
Coastal Sediments ◽  
Copper Mining ◽  
Mining District ◽  
Santa Rosalia
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