A land cover map of Latin America and the Caribbean in the framework of the SERENA project

Blanco, Paula Daniela; Colditz, René R.; Saldaña, Gerardo López; Hardtke, Leonardo Andrés; Llamas, Ricardo M.; Mari, Nicolas; Fischer, Angeles; Caride, Constanza; Aceñolaza, Pablo Gilberto; Valle, Héctor F. del; Lillo‐Saavedra, Mario; Coronato, Fernando Raúl; Opazo, Sergio; Morelli, Fabiano; Anaya, Jesús A.; Sione, Walter Fabian; Zamboni, Pamela; Arroyo, Víctor

doi:10.1016/j.rse.2012.12.025

Cited by 53 publications

(52 citation statements)

References 55 publications

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“…Studies using daily MODIS data have shown that, for the year 2008, there were insufficient valid observations for 4.1% of the area of Colombia [6]. This same study, however, allowed temporal interpolation across several months, i.e., also performing image classification in area with just 3-4 valid observations for the entire year.…”

Section: Discussionmentioning

confidence: 95%

“…Confidence maps have been successfully used in several remote sensing studies to describe areas of higher uncertainties in class assignment, area calculation, and assessing map accuracy or performing map comparison [6,7,54]. Lower confidences are expected in case of ambiguity in class assignment, either due to an unclear description by the explanatory variable set or highly fragmented, fine-scale structures.…”

Section: Classificationmentioning

confidence: 99%

“…Other land cover maps for Colombia are available at the continental scale for South America [3][4][5], Latin America and the Caribbean [6,7], and the globe [8][9][10][11][12] (Table 1). The generation of land cover maps using optical data in areas with persistent clouds is challenging [13].…”

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confidence: 99%

“…The generation of land cover maps using optical data in areas with persistent clouds is challenging [13]. For instance, filtering daily Moderate Resolution Imaging Spectroradiometer (MODIS) data over Colombia for the entire year of 2008 resulted in an area of 4.1% without any valid information, mainly due to clouds along the Pacific coast and in the Andean cordilleras [6]. At tropical latitudes MODIS acquires images at least every other day.…”

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confidence: 99%

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Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series

2015

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Abstract:Generating annual land cover maps in the tropics based on optical data is challenging because of the large amount of invalid observations resulting from the presence of clouds and haze or high moisture content in the atmosphere. This study proposes a strategy to build an annual time series from multi-year data to fill data gaps. The approach was tested using the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index and spectral bands as input for land cover classification of Colombia. In a second step, selected ancillary variables, such as elevation, L-band Radar, and precipitation were added to improve overall accuracy. Decision-tree classification was used for assigning eleven land cover classes using the International Geosphere-Biosphere Programme (IGBP) legend. Maps were assessed by their spatial confidence derived from the decision tree approach and conventional accuracy measures using reference data and statistics based on the error matrix. The multi-year data integration approach drastically decreased the area covered by invalid pixels. Overall accuracy of land cover maps significantly increased from 58.36% using only optical time series of 2011 filtered for low quality observations, to 68.79% when using data for 2011¨2 years. Adding elevation to the feature set resulted in 70.50% accuracy.

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Section: Discussionmentioning

confidence: 95%

Section: Classificationmentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series

2015

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“…Nevertheless, because available global land cover products are still limited thematically, continuous efforts to improve the LULC products are being made (Blanco et al, 2010;Colditz et al, 2011;Fernandes et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Deriving a per-field land use and land cover map in an agricultural mosaic catchment

Seo

Bogner

Poppenborg

et al. 2014

Earth Syst. Sci. Data

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Abstract. Detailed data on land use and land cover constitute important information for Earth system models, environmental monitoring and ecosystem services research. Global land cover products are evolving rapidly; however, there is still a lack of information particularly for heterogeneous agricultural landscapes. We censused land use and land cover field by field in the agricultural mosaic catchment Haean in South Korea. We recorded the land cover types with additional information on agricultural practice. In this paper we introduce the data, their collection and the post-processing protocol. Furthermore, because it is important to quantitatively evaluate available land use and land cover products, we compared our data with the MODIS Land Cover Type product (MCD12Q1). During the studied period, a large portion of dry fields was converted to perennial crops. Compared to our data, the forested area was underrepresented and the agricultural area overrepresented in MCD12Q1. In addition, linear landscape elements such as waterbodies were missing in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research. The data are available at the public repository Pangaea

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Spatial and temporal contrasts in the distribution of crops and pastures across Amazonia: A new agricultural land use data set from census data since 1950

Imbach

Manrow

Barona³

et al. 2015

Global Biogeochemical Cycles

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Amazonia holds the largest continuous area of tropical forests with intense land use change dynamics inducing water, carbon, and energy feedbacks with regional and global impacts. Much of our knowledge of land use change in Amazonia comes from studies of the Brazilian Amazon, which accounts for two thirds of the region. Amazonia outside of Brazil has received less attention because of the difficulty of acquiring consistent data across countries. We present here an agricultural statistics database of the entire Amazonia region, with a harmonized description of crops and pastures in geospatial format, based on administrative boundary data at the municipality level. The spatial coverage includes countries within Amazonia and spans censuses and surveys from 1950 to 2012. Harmonized crop and pasture types are explored by grouping annual and perennial cropping systems, C3 and C4 photosynthetic pathways, planted and natural pastures, and main crops. Our analysis examined the spatial pattern of ratios between classes of the groups and their correlation with the agricultural extent of crops and pastures within administrative units of the Amazon, by country, and census/survey dates. Significant correlations were found between all ratios and the fraction of agricultural lands of each administrative unit, with the exception of planted to natural pastures ratio and pasture lands extent. Brazil and Peru in most cases have significant correlations for all ratios analyzed even for specific census and survey dates. Results suggested improvements, and potential applications of the database for carbon, water, climate, and land use change studies are discussed. The database presented here provides an Amazon-wide improved data set on agricultural dynamics with expanded temporal and spatial coverage.Key Points Agricultural census database covers Amazon basin municipalities from 1950 to 2012Harmonized database groups crops and pastures by cropping system, C3/C4, and main cropsWe explored correlations between groups and the extent of agricultural lands

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A land cover map of Latin America and the Caribbean in the framework of the SERENA project

Cited by 53 publications

References 55 publications

Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series

Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series

Deriving a per-field land use and land cover map in an agricultural mosaic catchment

Spatial and temporal contrasts in the distribution of crops and pastures across Amazonia: A new agricultural land use data set from census data since 1950

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