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Support vector regression and synthetically mixed training data for quantifying urban land cover
Exploiting imaging spectrometer data with machine learning algorithms has been demonstrated to be an excellent choice for mapping …
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Mapping the extent of abandoned farmland in Central and Eastern Europe using MODIS time series satellite data
The demand for agricultural products continues to grow rapidly, but further agricultural expansion entails substantial environmental …
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Urban vegetation classification: Benefits of multitemporal RapidEye satellite data
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Modelling species distributions with remote sensing data: bridging disciplinary perspectives
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Ground-Based Hyperspectral Characterization of Alaska Tundra Vegetation along Environmental Gradients
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Import Vector Machines for Quantitative Analysis of Hyperspectral Data
In this letter we explore probabilities derived from an import vector machines (IVM) classifier as quantitative measures of class …
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A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models
We present an integrated modeling framework for simulating land-use decision making under the influence of payments for ecosystem …
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Landsat-based mapping of post-Soviet land-use change to assess the effectiveness of the Oksky and Mordovsky protected areas in European Russia
Land-use and land-cover change (LULCC) is the main cause of the global biodiversity crisis and protected areas are critical to prevent …
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Mapping Rubber Plantations and Natural Forests in Xishuangbanna (Southwest China) Using Multi-Spectral Phenological Metrics from MODIS Time Series
We developed and evaluated a new approach for mapping rubber plantations and natural forests in one of Southeast Asia’s biodiversity …
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Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees
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