Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series
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{"title"=>"Characterizing forest change using community-based monitoring data and landsat time series", "type"=>"journal", "authors"=>[{"first_name"=>"Ben", "last_name"=>"Devries", "scopus_author_id"=>"56538797300"}, {"first_name"=>"Arun Kumar", "last_name"=>"Pratihast", "scopus_author_id"=>"50361758300"}, {"first_name"=>"Jan", "last_name"=>"Verbesselt", "scopus_author_id"=>"12645007600"}, {"first_name"=>"Lammert", "last_name"=>"Kooistra", "scopus_author_id"=>"6603894270"}, {"first_name"=>"Martin", "last_name"=>"Herold", "scopus_author_id"=>"7102192954"}], "year"=>2016, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84962135861", "sgr"=>"84962135861", "issn"=>"19326203", "pui"=>"609350856", "isbn"=>"1932-6203<br />", "doi"=>"10.1371/journal.pone.0147121"}, "id"=>"b13298ca-9ddf-305d-ad6f-7caf2a51e8ab", "abstract"=>"Increasing awareness of the issue of deforestation and degradation in the tropics has resulted in efforts to monitor forest resources in tropical countries. Advances in satellite-based remote sensing and ground-based technologies have allowed for monitoring of forests with high spatial, temporal and thematic detail. Despite these advances, there is a need to engage communities in monitoring activities and include these stakeholders in national forest monitoring systems. In this study, we analyzed activity data (deforestation and forest degradation) collected by local forest experts over a 3-year period in an Afro-montane forest area in southwestern Ethiopia and corresponding Landsat Time Series (LTS). Local expert data included forest change attributes, geo-location and photo evidence recorded using mobile phones with integrated GPS and photo capabilities. We also assembled LTS using all available data from all spectral bands and a suite of additional indices and temporal metrics based on time series trajectory analysis. We predicted deforestation, degradation or stable forests using random forest models trained with data from local experts and LTS spectral-temporal metrics as model covariates. Resulting models predicted deforestation and degradation with an out of bag (OOB) error estimate of 29% overall, and 26% and 31% for the deforestation and degradation classes, respectively. By dividing the local expert data into training and operational phases corresponding to local monitoring activities, we found that forest change models improved as more local expert data were used. Finally, we produced maps of deforestation and degradation using the most important spectral bands. The results in this study represent some of the first to combine local expert based forest change data and dense LTS, demonstrating the complementary value of both continuous data streams. Our results underpin the utility of both datasets and provide a useful foundation for integrated forest monitoring systems relying on data streams from diverse sources.", "link"=>"http://www.mendeley.com/research/characterizing-forest-change-using-communitybased-monitoring-data-landsat-time-series", "reader_count"=>105, "reader_count_by_academic_status"=>{"Unspecified"=>4, "Professor > Associate Professor"=>4, "Student > Doctoral Student"=>10, "Researcher"=>23, "Student > Ph. D. Student"=>27, "Student > Postgraduate"=>5, "Student > Master"=>21, "Other"=>5, "Student > Bachelor"=>5, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>4, "Professor > Associate Professor"=>4, "Student > Doctoral Student"=>10, "Researcher"=>23, "Student > Ph. D. Student"=>27, "Student > Postgraduate"=>5, "Student > Master"=>21, "Other"=>5, "Student > Bachelor"=>5, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>9, "Engineering"=>4, "Environmental Science"=>50, "Agricultural and Biological Sciences"=>14, "Physics and Astronomy"=>1, "Social Sciences"=>8, "Computer Science"=>1, "Earth and Planetary Sciences"=>18}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Social Sciences"=>{"Social Sciences"=>8}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>18}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>14}, "Computer Science"=>{"Computer Science"=>1}, "Unspecified"=>{"Unspecified"=>9}, "Environmental Science"=>{"Environmental Science"=>50}}, "reader_count_by_country"=>{"Netherlands"=>2, "United States"=>1, "United Kingdom"=>1, "Slovakia"=>1, "Germany"=>1, "Spain"=>2}, "group_count"=>3}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/4873876"], "description"=>"<p>Importance scores (<i>S</i>) for each band based on overall accuracies and class accuracies for deforestation (DEF), degradation (DEG) and no-change (NOCH).</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133411, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g008", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Importance_scores_i_S_i_for_each_band_based_on_overall_accuracies_and_class_accuracies_for_deforestation_DEF_degradation_DEG_and_no_change_NOCH_/3133411", "title"=>"Importance scores (<i>S</i>) for each band based on overall accuracies and class accuracies for deforestation (DEF), degradation (DEG) and no-change (NOCH).", "pos_in_sequence"=>9, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873984"], "description"=>"<p>Random forest class probability histograms for deforestation (red) and degradation (blue) at each of the four sites shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147121#pone.0147121.g009\" target=\"_blank\">Fig 9</a>.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133510, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g010", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Random_forest_class_probability_histograms_for_deforestation_red_and_degradation_blue_at_each_of_the_four_sites_shown_in_Fig_9_/3133510", "title"=>"Random forest class probability histograms for deforestation (red) and degradation (blue) at each of the four sites shown in Fig 9.", "pos_in_sequence"=>11, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873684"], "description"=>"<p>The location shown in panel A corresponds to the time series shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147121#pone.0147121.g004\" target=\"_blank\">Fig 4</a>, and the location shown in panel B corresponds to the time series shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147121#pone.0147121.g005\" target=\"_blank\">Fig 5</a>.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133222, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g003", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Photo_evidence_from_local_disturbance_reports_documenting_deforestation_A_and_degradation_B_/3133222", "title"=>"Photo evidence from local disturbance reports documenting deforestation (A) and degradation (B).", "pos_in_sequence"=>4, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873921"], "description"=>"<p>The probability of deforestation and degradation are shown as red and blue colour maps, respectively. Local expert reports of deforestation (X) or degradation (+) collected between 2012 and 2015 are overlaid on the maps. The base images are SPOT5 images (band 2; 2.5m spatial resolution) acquired between 2009 and 2011. Dark shaded areas represent forest in the SPOT5 image, and light areas are non-forest land cover types (e.g. cropland or wetland). The locations of each tile (A to D) are shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147121#pone.0147121.g001\" target=\"_blank\">Fig 1</a>.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133447, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g009", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Maps_of_deforestation_and_degradation_at_four_sites_/3133447", "title"=>"Maps of deforestation and degradation at four sites.", "pos_in_sequence"=>10, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873750"], "description"=>"<p>The RLM-fitted season-trend model for each segment is shown as a dotted line. Local disturbance photo evidence for this site is shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147121#pone.0147121.g003\" target=\"_blank\">Fig 3B</a>.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133288, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g005", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Time_series_over_a_degraded_forest_site_for_four_spectral_bands_SWIR2_NDVI_NBR_and_TCW_/3133288", "title"=>"Time series over a degraded forest site for four spectral bands: SWIR2, NDVI, NBR and TCW.", "pos_in_sequence"=>6, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4874026"], "description"=>"<p>Spectral bands on the Landsat TM, ETM+ and OLI sensors.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133549, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.t001", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Spectral_bands_on_the_Landsat_TM_ETM_and_OLI_sensors_/3133549", "title"=>"Spectral bands on the Landsat TM, ETM+ and OLI sensors.", "pos_in_sequence"=>12, "defined_type"=>3, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4874056"], "description"=>"<p>Spectral indices used in this study.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133582, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.t002", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Spectral_indices_used_in_this_study_/3133582", "title"=>"Spectral indices used in this study.", "pos_in_sequence"=>13, "defined_type"=>3, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873588"], "description"=>"<p>Biosphere Reserve zones and location of local expert disturbance reports (deforestation and degradation) and additional reference data (no-change) are shown. The locations of map tiles from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147121#pone.0147121.g009\" target=\"_blank\">Fig 9</a> are shown as boxes labeled A to D.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133135, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g001", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Study_area_located_in_the_UNESCO_Kafa_Biosphere_Reserve_in_the_Southern_Nations_Nationalities_and_Peoples_Republic_SNNPR_state_of_southwestern_Ethiopia_/3133135", "title"=>"Study area located in the UNESCO Kafa Biosphere Reserve in the Southern Nations, Nationalities and Peoples Republic (SNNPR) state of southwestern Ethiopia.", "pos_in_sequence"=>2, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873717"], "description"=>"<p>The RLM-fitted season-trend model for each segment is shown as a dotted line. Local disturbance photo evidence for this site is shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147121#pone.0147121.g003\" target=\"_blank\">Fig 3A</a>.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133264, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g004", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Time_series_over_a_deforested_site_for_four_spectral_bands_SWIR2_NDVI_NBR_and_TCW_/3133264", "title"=>"Time series over a deforested site for four spectral bands: SWIR2, NDVI, NBR and TCW.", "pos_in_sequence"=>5, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873495", "https://ndownloader.figshare.com/files/4873513", "https://ndownloader.figshare.com/files/4873525"], "description"=>"<div><p>Increasing awareness of the issue of deforestation and degradation in the tropics has resulted in efforts to monitor forest resources in tropical countries. Advances in satellite-based remote sensing and ground-based technologies have allowed for monitoring of forests with high spatial, temporal and thematic detail. Despite these advances, there is a need to engage communities in monitoring activities and include these stakeholders in national forest monitoring systems. In this study, we analyzed activity data (deforestation and forest degradation) collected by local forest experts over a 3-year period in an Afro-montane forest area in southwestern Ethiopia and corresponding Landsat Time Series (LTS). Local expert data included forest change attributes, geo-location and photo evidence recorded using mobile phones with integrated GPS and photo capabilities. We also assembled LTS using all available data from all spectral bands and a suite of additional indices and temporal metrics based on time series trajectory analysis. We predicted deforestation, degradation or stable forests using random forest models trained with data from local experts and LTS spectral-temporal metrics as model covariates. Resulting models predicted deforestation and degradation with an out of bag (OOB) error estimate of 29% overall, and 26% and 31% for the deforestation and degradation classes, respectively. By dividing the local expert data into training and operational phases corresponding to local monitoring activities, we found that forest change models improved as more local expert data were used. Finally, we produced maps of deforestation and degradation using the most important spectral bands. The results in this study represent some of the first to combine local expert based forest change data and dense LTS, demonstrating the complementary value of both continuous data streams. Our results underpin the utility of both datasets and provide a useful foundation for integrated forest monitoring systems relying on data streams from diverse sources.</p></div>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133078, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0147121.s001", "https://dx.doi.org/10.1371/journal.pone.0147121.s002", "https://dx.doi.org/10.1371/journal.pone.0147121.s003"], "stats"=>{"downloads"=>3, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Characterizing_Forest_Change_Using_Community_Based_Monitoring_Data_and_Landsat_Time_Series/3133078", "title"=>"Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series", "pos_in_sequence"=>1, "defined_type"=>4, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873795"], "description"=>"<p>Time of acquisition of local expert data (parallelograms) are shown in the box on the right hand side. In each phase, a subset of the local expert data were used for model calibration (grey), and another subset was used for model validation (white).</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133336, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g006", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Flowchart_demonstrating_the_iterative_updating_of_random_forest_models_/3133336", "title"=>"Flowchart demonstrating the iterative updating of random forest models.", "pos_in_sequence"=>7, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873633"], "description"=>"<p>Processes are shown as rectangles and data and results are shown as parallelograms.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133177, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g002", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Flowchart_of_methods_used_in_this_study_/3133177", "title"=>"Flowchart of methods used in this study.", "pos_in_sequence"=>3, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/4873834"], "description"=>"<p>Boxplots of random forest class probabilities for the deforestation (<i>P</i>(<i>DEF</i>)), degradation (<i>P</i>(<i>DEG</i>)) or no-change (<i>P</i>(<i>NOCH</i>)) computed for <i>in situ</i> data having DEF or DEG labels are shown for the training phase (top panel) and operational phase (bottom panel) of the monitoring activities. The model updating approach is shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147121#pone.0147121.g006\" target=\"_blank\">Fig 6</a>.</p>", "links"=>[], "tags"=>["monitoring activities", "degradation", "forest change models", "GPS", "forest change data", "forest change attributes", "forest monitoring systems", "LTS", "data streams", "Landsat Time Series", "expert data", "Local expert data", "deforestation", "OOB", "time series trajectory analysis"], "article_id"=>3133375, "categories"=>["Environmental Sciences not elsewhere classified", "Ecology", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Ben DeVries", "Arun Kumar Pratihast", "Jan Verbesselt", "Lammert Kooistra", "Martin Herold"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0147121.g007", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Iterative_calibration_and_validation_of_change_classes_/3133375", "title"=>"Iterative calibration and validation of change classes.", "pos_in_sequence"=>8, "defined_type"=>1, "published_date"=>"2016-03-28 06:03:22"}

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{"start_date"=>"2016-01-01T00:00:00Z", "end_date"=>"2016-12-31T00:00:00Z", "subject_areas"=>[]}
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