Good practices for estimating area and assessing accuracy of land change
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Land claim and loss of tidal flats in the Yangtze Estuary.A contemporary decennial examination of changing agricultural field sizes using Landsat time series dataRapid conversions and avoided deforestation: examining four decades of industrial plantation expansion in Borneo.Pushing the Limits: The Pattern and Dynamics of Rubber Monoculture Expansion in Xishuangbanna, SW ChinaTypes and rates of forest disturbance in Brazilian Legal Amazon, 2000-2013Rates and drivers of mangrove deforestation in Southeast Asia, 2000-2012Carbon emissions from agricultural expansion and intensification in the Chaco.Choice of satellite imagery and attribution of changes to disturbance type strongly affects forest carbon balance estimates.Cropland changes in times of conflict, reconstruction, and economic development in Iraqi KurdistanHarmonization of forest disturbance datasets of the conterminous USA from 1986 to 2011.A global view of shifting cultivation: Recent, current, and future extent.Inconsistent estimates of forest cover change in China between 2000 and 2013 from multiple datasets: differences in parameters, spatial resolution, and definitions.Conservation performance of different conservation governance regimes in the Peruvian Amazon.A large-area, spatially continuous assessment of land cover map error and its impact on downstream analyses.Spatial distribution of young forests and carbon fluxes within recent disturbances in Russia.Forest loss in New England: A projection of recent trends.Tropical forests are a net carbon source based on aboveground measurements of gain and loss.Spatial patterns of the United States National Land Cover Dataset (NLCD) land-cover change thematic accuracy (2001-2011).Potential of remote sensing to predict species invasionsSpectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) dataSecondary Forest and Shrubland Dynamics in a Highly Transformed Landscape in the Northern Andes of Colombia (1985–2015)Using Space-Time Features to Improve Detection of Forest Disturbances from Landsat Time SeriesA Bayesian Approach to Combine Landsat and ALOS PALSAR Time Series for Near Real-Time Deforestation DetectionComparing Quantity, Allocation and Configuration Accuracy of Multiple Land Change ModelsMonitoring selective logging with Landsat satellite imagery reveals that protected forests in Western Siberia experience greater harvest than non-protected forestsCharacterizing Degradation Gradients through Land Cover Change Analysis in Rural Eastern Cape, South AfricaLand Cover Classification in an Ecuadorian Mountain Geosystem Using a Random Forest Classifier, Spectral Vegetation Indices, and Ancillary Geographic DataAn Operational Framework for Land Cover Classification in the Context of REDD+ Mechanisms. A Case Study from Costa RicaAnalysing Spatial and Statistical Dependencies of Deforestation Affected by Residential Growth: Gorganrood Basin, Northeast IranComment on Gebhardt et al. MAD-MEX: Automatic Wall-to-Wall Land Cover Monitoring for the Mexican REDD-MRV Program Using All Landsat Data. Remote Sens. 2014, 6, 3923–3943LACO-Wiki: A New Online Land Cover Validation Tool Demonstrated Using GlobeLand30 for KenyaTree Species Abundance Predictions in a Tropical Agricultural Landscape with a Supervised Classification Model and Imbalanced DataUsing a global reference sample set and a cropland map for area estimation in ChinaTowards a common validation sample set for global land-cover mappingCombining Spectral Data and a DSM from UAS-Images for Improved Classification of Non-Submerged Aquatic VegetationDifferentiation of Alternate Harvesting Practices Using Annual Time Series of Landsat DataMass data processing of time series Landsat imagery: pixels to data products for forest monitoringIntegrated Object-Based Spatiotemporal Characterization of Forest Change from an Annual Time Series of Landsat Image CompositesLarge Area Mapping of Annual Land Cover Dynamics Using Multitemporal Change Detection and Classification of Landsat Time Series DataForest Monitoring Using Landsat Time Series Data: A Review
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Good practices for estimating area and assessing accuracy of land change
description
article
@en
wetenschappelijk artikel
@nl
наукова стаття, опублікована в травні 2014
@uk
name
Good practices for estimating area and assessing accuracy of land change
@en
Good practices for estimating area and assessing accuracy of land change
@nl
type
label
Good practices for estimating area and assessing accuracy of land change
@en
Good practices for estimating area and assessing accuracy of land change
@nl
prefLabel
Good practices for estimating area and assessing accuracy of land change
@en
Good practices for estimating area and assessing accuracy of land change
@nl
P2093
P50
P1476
Good practices for estimating area and assessing accuracy of land change
@en
P2093
Curtis E. Woodcock
Pontus Olofsson
Stephen V. Stehman
P356
10.1016/J.RSE.2014.02.015
P577
2014-05-01T00:00:00Z