{"id":34,"date":"2026-04-09T23:00:18","date_gmt":"2026-04-09T23:00:18","guid":{"rendered":"https:\/\/colombia.alerta.mapbiomas.org\/?page_id=34"},"modified":"2026-04-27T16:43:04","modified_gmt":"2026-04-27T16:43:04","slug":"metodo-mapbiomas-alerta","status":"publish","type":"page","link":"https:\/\/colombia.alerta.mapbiomas.org\/en\/metodo-mapbiomas-alerta\/","title":{"rendered":"Method MapBiomas Alerta"},"content":{"rendered":"<style>\n.alert-table.wp-block-table td, .alert-table.wp-block-table th {\n    border: 0;\n}\n\n.alert-table.wp-block-table tr:first-child td {\n    text-align: center;\n    background-color: #8b3323;\n    border-right: 1px solid #ffffff;\n    color: #ffffff;\n}\n\n.alert-table.wp-block-table tr:first-child td:last-child {\n    border-right: 0;\n}\n\n.alert-table.wp-block-table tbody tr:not(:first-child) {\n    border-bottom: 1px solid #000000;\n}\n\n.alert-table.wp-block-table tr:not(:first-child) td:first-child {\n    font-weight: bold;\n    color: #8b3323;\n}\n<\/style>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>GET TO KNOW MAPBIOMAS ALERTA METHOD<\/strong><\/h4>\n\n\n\n<p>MapBiomas Alerta is a validation and publication system that compiles and integrates alerts from different national and global sources of deforestation and natural vegetation cover loss detection, based on remote sensing techniques and computer-aided interpretation and supervised classification. This set of alerts undergoes processes of aggregation, validation by comparison using high-resolution satellite imagery (PlanetScope, with a spatial resolution of 3.7 m), refinement, auditing, and publication of each alert (event by event). From this procedure, an exact delimitation of the affected areas, date of occurrence, driving trend of the cause, and intersection with territorial geographical information are obtained, available in detailed technical reports, consolidated through a single open-access platform:<br><br><a href=\"https:\/\/plataforma.colombia.alerta.mapbiomas.org\/\">https:\/\/plataforma.colombia.alerta.mapbiomas.org\/<\/a><\/p>\n\n\n\n<p>MapBiomas Alerta processing methodology is described below:<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>VALIDATION, REFINEMENT, AND PUBLICATION SYSTEM FOR PRE-EXISTING DEFORESTATION ALERTS&nbsp;<\/strong><\/h4>\n\n\n\n<p>MapBiomas Alerta is a system that operates through a six-step process: compilation (search, download, preparation, and upload to the platform), validation (comparison with high-resolution imagery), refinement (delimitation of the polygon with high-resolution imagery), intersection with public data (political-administrative division, Protected Areas, and Collective Territories, among others), auditing (review by a third-party expert), and publication of deforestation and vegetation cover loss alerts, with their respective reports (Figure 1).<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" loading=\"lazy\" width=\"1024\" height=\"609\" src=\"https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/metodoingles.png\" alt=\"\" class=\"wp-image-287\" srcset=\"https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/metodoingles.png 1275w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/metodoingles-300x177.png 300w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/metodoingles-1024x605.png 1024w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/metodoingles-768x454.png 768w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/metodoingles-18x12.png 18w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p><strong>Figure 1.<\/strong> Methodological process of MapBiomas Alerta for the compilation, validation, refinement, data intersection, auditing, and publication of deforestation events and loss of natural cover in Colombia.<\/p>\n\n\n\n<p><strong>Step 1: Compilation of deforestation alerts and natural vegetation cover loss alerts from different satellite monitoring systems <\/strong><strong>natural provenientes de diferentes sistemas de monitoreo satelital<\/strong><\/p>\n\n\n\n<p>MapBiomas Alerta gathers, organizes, and consolidates information from various official and independent monitoring systems at the national and global levels that detect and publish deforestation alerts and natural vegetation cover losses in the natural regions of Colombia (Amazon, Andes, Caribbean, Orinoqu\u00eda, and Pacific). These systems employ data with different spatial resolutions (between 10 and 30 meters) to generate the alerts; this information is compiled by professionals from the MapBiomas Alerta Colombia project (Table 1). MapBiomas Alerta consults and processes the alerts issued by Global Land Analysis &amp; Discovery Sentinel (GLAD-S), Global Land Analysis &amp; Discovery Landsat (GLAD-L), Radar for Detecting Deforestation (RADD), GAIA, The land disturbance product (DIST), and Land Use Change Alerts (LUCA), and the alerts published quarterly by the Forest and Carbon Monitoring System (SMByC) of the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM):<br><br>Tabla 1: Sources and systems for detecting deforestation in Colombia compiled by MapBiomas Alerta.<\/p>\n\n\n\n<figure class=\"wp-block-table alert-table\"><table><tbody><tr><td><strong>Monitoring system<\/strong><\/td><td><strong>Definition<\/strong><\/td><td><strong>Source<\/strong><\/td><td><strong>Operating period<\/strong><\/td><td><strong>Satellite system<\/strong><\/td><td><strong>Update<\/strong><\/td><td><strong>Coverage<\/strong><\/td><\/tr><tr><td><strong>GLAD-L<\/strong> <strong>\/<\/strong> <strong>GLAD-S2<\/strong><\/td><td>Global Land Analysis &amp; Discover<\/td><td>University of Maryland<\/td><td>2015 \u2013 present<\/td><td>Landsat (30m)<br>Sentinel-2 (10m)<\/td><td>Every 8 and 5 days<\/td><td>Tropical forests<\/td><\/tr><tr><td><strong>RADD<\/strong><\/td><td>Radar Alerts for Deforestation Detection<\/td><td>Wageningen University &amp; Research and Satelligence<\/td><td>2019 \u2013 present<\/td><td>Sentinel-1 (10m)<\/td><td>Every 6\u201312 days<\/td><td>The Amazon Basin, Sub-Saharan Africa, and Insular Southeast Asia<\/td><\/tr><tr><td><strong>SMByC<\/strong><\/td><td>Colombia's Forest and Carbon Monitoring Systems<\/td><td>IDEAM<\/td><td>2012 \u2013 present<\/td><td>Landsat (30m)<\/td><td>Annual<\/td><td>Colombia<\/td><\/tr><tr><td><strong>Terra-i<\/strong><\/td><td>A near-real-time monitoring system for habitat loss in Latin America<\/td><td>CIAT<\/td><td>2000 \u2013 2024<\/td><td>MODIS (250m)<\/td><td>Every 16 days<\/td><td>Latin America&nbsp;<\/td><\/tr><tr><td><strong>FORMA<\/strong><\/td><td>Forest Monitoring for Action<\/td><td>World Resource Institute<\/td><td>2006 &#8211; 2017<\/td><td>MODIS (300m-1km)<\/td><td>Monthly<\/td><td>Asia, Latin America, Africa<\/td><\/tr><tr><td><strong>JJ-FAST<\/strong><\/td><td>Warning System in the Tropics<\/td><td>JICA\/JAXA Japan<\/td><td>2016 \u2013 present<\/td><td>ALOS-2 (3-10m)<\/td><td>1.5 months<\/td><td>Tropical forests<\/td><\/tr><tr><td><strong>LUCA<\/strong><\/td><td>Land Use Change Alerts<\/td><td>CTrees<\/td><td>2018 \u2013 present<\/td><td>Sentinel-1 C-band Synthetic Aperture Radar (SAR)<\/td><td>Every two weeks<\/td><td>Forest areas, including humid tropical, dry tropical, temperate, and boreal biomes<\/td><\/tr><tr><td><strong>DIST<\/strong><\/td><td>Land Surface Disturbance Alert<\/td><td>University of Maryland<\/td><td>2023 \u2013 present<\/td><td>Harmonized Landsat and Sentinel-2 (HLS)<\/td><td>Every two weeks<\/td><td>Areas with vegetation on every continent&nbsp;<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><strong>Step 2: Validation and selection of imagery before and after the natural vegetation cover loss event<\/strong><\/p>\n\n\n\n<p>The validation process is carried out in two stages. The first is semi-automatic through an integrated platform with infrastructure that consumes daily PlanetScope imagery. Within it, two core processes are developed:<br><br><strong>1. Semi-automated filtering and debugging:<\/strong> The system, supported by an infrastructure that integrates daily PlanetScope images, automatically discards alerts superimposed over others that have already been validated, refined, or published previously, thus avoiding duplication of information.<\/p>\n\n\n\n<p><strong>2. Visual inspection by experts:<\/strong> Specialized analysts at the regional level (Amazon, Andes, Caribbean, Pacific, and Orinoqu\u00eda) perform an exhaustive review using monthly high-resolution mosaics (3.7 meters).<\/p>\n\n\n\n<p>In this phase, false positives are identified and discarded, formally recording the cause of rejection, based on the following criteria:&nbsp;<\/p>\n\n\n\n<ul>\n<li><strong>Duplicity:<\/strong> Polygons that correspond to the same event detected by multiple sources.<\/li>\n\n\n\n<li><strong>Seasonality:<\/strong> Changes in the spectral response of the images due to droughts or floods that do not involve the loss of forest or natural vegetation.<\/li>\n\n\n\n<li><strong>Previous land use intervention or alteration:<\/strong> Areas that had already been transformed or correspond to secondary vegetation.<\/li>\n\n\n\n<li><strong>Burnings:<\/strong> Areas where fires are recorded; in cases where no subsequent use is evidenced, such areas will be considered unauthorized and will be rejected.<\/li>\n<\/ul>\n\n\n\n<p><strong>Selection of satellite evidence:<\/strong> When visual inspection confirms a change event in natural vegetation cover, two daily images from the Planet constellation are consulted and acquired under an exclusive contract: one of the \"before\" (intact forest or vegetation) and another of the \"after\" (transformed area).<\/p>\n\n\n\n<p>To guarantee adequate detail in the reports, the following technical criteria are used:<\/p>\n\n\n\n<ul>\n<li><strong>Territorial Context: <\/strong>The image capture covers a minimum area of 700 x 700 meters (square), centering the event to provide a clear view of the affected environment.<\/li>\n\n\n\n<li><strong>Critical Temporality:<\/strong> Priority is given to ensuring the time interval between both images is as short as possible (with a maximum allowed of one year) to accurately document the speed of deforestation.<\/li>\n\n\n\n<li><strong>Image Quality:<\/strong> The absence of clouds, haze, or processing errors (banding or displacement) is audited.<\/li>\n<\/ul>\n\n\n\n<p><strong>Step 3: Refinement using high-resolution imagery<\/strong><\/p>\n\n\n\n<p>Once the validity of the event is confirmed and the satellite evidence is selected, the transformed area is delimited. This spatial refinement process converts the initial detection into an exact polygon that represents the actual shape and pattern of the natural vegetation loss.<\/p>\n\n\n\n<p>This refinement is carried out through a semi-automatic classification process that improves the definition of the contours where the change in natural vegetation cover occurred. For this purpose, a supervised classification algorithm (<em>Random Forest<\/em>is used, running on <em>Google Earth Engine<\/em> through a work module (<em>Workspace<\/em>) designed by MapBiomas to process these alerts.<\/p>\n\n\n\n<ul>\n<li><strong>Sampling on intact surfaces: <\/strong>Pixels representing conserved forest, secondary vegetation, water surfaces, existing roads, or urban soils.<\/li>\n\n\n\n<li><strong>Sampling on transformed surfaces:<\/strong> Pixels showing the recent removal of the remaining natural cover.<\/li>\n<\/ul>\n\n\n\n<p>The result is a refined polygon that is subsequently subjected to two technical optimization processes of simplification and cleaning to eliminate unnecessary vertices and isolated residual polygons with a minimum area that is lower than or not part of the main disturbance.&nbsp;<\/p>\n\n\n\n<p>Finally, with the defined polygon and based on photo-interpretation and contextual reference information at the \"before\" and \"after\" moments, a pressure vector or probable driving factor of the transformation is assigned. These vectors are categorized into the following categories:&nbsp;<\/p>\n\n\n\n<p><strong>1. Anthropic Vectors&nbsp;<\/strong><\/p>\n\n\n\n<p>Transformation of the forest or natural covers for:<\/p>\n\n\n\n<ul>\n<li>Livestock Farming: Pastures for cattle ranching.<\/li>\n\n\n\n<li>Agriculture: Subsistence or industrial crops.<\/li>\n\n\n\n<li>Mining: Mineral extraction (gold, coal, etc.), whether alluvial (in river floodplains) or open-pit.<\/li>\n\n\n\n<li>Road opening: New linear patterns, construction of roads or airstrips.<\/li>\n\n\n\n<li>Urban expansion: Growth of populated centers.<\/li>\n\n\n\n<li>Indigenous  cultural use: Rotational subsistence cultivation system (chagra) characteristic of indigenous peoples<\/li>\n\n\n\n<li>Forest plantation: Forest crops for commercial purposes aimed at obtaining and marketing timber products and cellulose pulp for paper.&nbsp;<\/li>\n\n\n\n<li>Aquaculture: Controlled water bodies for the rearing of hydrobiological species.<\/li>\n<\/ul>\n\n\n\n<p><strong>2. Natural Vectors<\/strong><\/p>\n\n\n\n<p>Transformation of the forest or natural covers by:<\/p>\n\n\n\n<ul>\n<li>Windsweeper: Massive falling of trees caused by high-intensity wind gusts, such as hurricanes or severe storms.<\/li>\n\n\n\n<li>Flooding: Loss of vegetation cover associated with the overflowing of water bodies.<\/li>\n\n\n\n<li>Landslide: Mass removal phenomenon associated with terrain instability, leading to the loss of natural vegetation cover, primarily in hillside areas.<\/li>\n<\/ul>\n\n\n\n<p>Each alert, after an initial audit of the images, may be reintroduced into the previous process for the following reasons: i) the images do not meet the standards for publication; ii) the selected area is too small and does not allow for adequate territorial contextualization; or iii) the event is not properly located within the selected area.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" loading=\"lazy\" width=\"1024\" height=\"561\" src=\"https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/image4.png\" alt=\"\" class=\"wp-image-289\" srcset=\"https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/image4.png 1999w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/image4-300x165.png 300w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/image4-1024x562.png 1024w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/image4-768x421.png 768w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/image4-1536x843.png 1536w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/image4-18x10.png 18w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>Figure 2. Example of satellite imagery before and after the deforestation event, with the refined polygon of the alert (ID 40155449).<\/p>\n\n\n\n<p><strong>Step 4: Cross-verification with public databases of secondary territorial information&nbsp;<\/strong><\/p>\n\n\n\n<p>The refined polygons are geographically intersected with layers of territorial and contextual information from various official entities (Table 2); these attributes are included in the reports with their respective intersection areas.<\/p>\n\n\n\n<p>Table 2: Public and official geographical layers compiled for the automatic intersection with each event reported in MapBiomas Alerta.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Institution<\/strong><\/td><td><strong>Official layer name<\/strong><\/td><td><strong>Year<\/strong><\/td><\/tr><tr><td rowspan=\"3\">Agencia Nacional de Tierras (ANT)<\/td><td>Peasant Reserve Zone<\/td><td>2018<\/td><\/tr><tr><td>Community Councils<\/td><td>2020<\/td><\/tr><tr><td>Indigenous Reserves<\/td><td>2025<\/td><\/tr><tr><td rowspan=\"2\">Departamento Administrativo Nacional de Estad\u00edstica y el Instituto Geogr\u00e1fico Agust\u00edn Codazzi (DANE\u2013IGAC)&nbsp;<\/td><td>Department<\/td><td rowspan=\"2\">2024<\/td><\/tr><tr><td>Municipality or ETI<\/td><\/tr><tr><td>Fundaci\u00f3n Gaia Amazonas (FGA)<\/td><td>Regions&nbsp;<\/td><td>2024<\/td><\/tr><tr><td><br>Instituto de Hidrolog\u00eda, Meteorolog\u00eda y Estudios Ambientales (IDEAM)<\/td><td>Hydrographic Basin Level 2<\/td><td><br><br>2024<\/td><\/tr><tr><td>Instituto Geogr\u00e1fico Agust\u00edn Codazzi (IGAC)<\/td><td>Cadastre<\/td><td>2020<\/td><\/tr><tr><td rowspan=\"3\">Unidad de Planificaci\u00f3n Rural Agropecuaria &#8211; (UPRA)<\/td><td>Agricultural Frontier<\/td><td>2025<\/td><\/tr><tr><td>Peasant Agro-food Territories<\/td><td>2025<\/td><\/tr><tr><td>Protection Zones for Food Production<\/td><td>2025<\/td><\/tr><tr><td rowspan=\"9\">Ministerio de Ambiente y Desarrollo Sostenible<\/td><td>Tropical Rainforest<\/td><td>2015<\/td><\/tr><tr><td>CAR Boundary (Regional Autonomous Corporation)<\/td><td>2019<\/td><\/tr><tr><td>P\u00e1ramos<\/td><td>2020<\/td><\/tr><tr><td>Forest Reserves (Law 2 of 1959)<\/td><td>2025<\/td><\/tr><tr><td>Forest Development and Biodiversity Hubs<\/td><td>2025<\/td><\/tr><tr><td>Forest Management Plans<\/td><td>2026<\/td><\/tr><tr><td>Environmental Sanctions<\/td><td>2026<\/td><\/tr><tr><td>Peace Forests<\/td><td>2023<\/td><\/tr><tr><td>Habitat Banks<\/td><td>2024<\/td><\/tr><tr><td>RAMSAR<\/td><td>Ramsar<\/td><td>2020<\/td><\/tr><tr><td rowspan=\"2\">Parques Nacionales Naturales. Registro Nacional de \u00c1reas Protegidas (RUNAP)&nbsp;<\/td><td>National Protected Natural Area<\/td><td rowspan=\"2\">2024<\/td><\/tr><tr><td>Departmental Protected Area<\/td><\/tr><tr><td>Instituto Amaz\u00f3nico de Investigaciones Cient\u00edficas SINCHI<\/td><td>Conservation Agreements&nbsp;<\/td><td>2026<\/td><\/tr><tr><td>Instituto de Investigaciones Marinas y Costeras Jos\u00e9 Benito Vives de Andr\u00e9is (INVEMAR)<\/td><td>Mangroves<\/td><td>2025<\/td><\/tr><tr><td rowspan=\"2\">Autoridad Nacional de Licencias Ambientales (ANLA)<\/td><td>Licensed Projects<\/td><td>2025<\/td><\/tr><tr><td>Projects Under Evaluation<\/td><td>2025<\/td><\/tr><tr><td>El Instituto de Investigaci\u00f3n de Recursos Biol\u00f3gicos Alexander von Humboldt (IAvH)<\/td><td>Wetlands<\/td><td>2016<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>This information allows for the characterization and contextualization of each alert, facilitating the generation of technical reports supported by official, updated, and relevant information for different purposes.<\/p>\n\n\n\n<p><strong>Update and curation protocol for territorial information layers<\/strong><\/p>\n\n\n\n<p>MapBiomas Alerta implements a continuous maintenance and update flow for its information layers to guarantee the validity of the territorial context with which the alerts are intersected.<\/p>\n\n\n\n<p>This process includes the constant integration of new geospatial datasets as official entities release them on public platforms or through direct coordination with the competent authorities when the information is not available in open repositories.<\/p>\n\n\n\n<p>MapBiomas Alerta performs curation that may include topological, geometric, or alignment adjustments with international boundaries, which are duly documented in the metadata. These technical refinements are shared with the source entities for their review, promoting constant feedback between civil society and institutional bodies.<\/p>\n\n\n\n<p>It is fundamental to highlight that these data harmonization procedures are governed by the principle of source integrity:<\/p>\n\n\n\n<ul>\n<li>Original content is not altered: no polygons are added to the primary data.<\/li>\n\n\n\n<li>Preservation of Attributes: Descriptive data assigned by the official entity remain intact without compromising sensitive statistical information.&nbsp;<\/li>\n<\/ul>\n\n\n\n<p>Technical Purpose: Adjustments are strictly limited to optimizing system functionality and the quality of the user visualization, without introducing substantial changes to the reported information.<\/p>\n\n\n\n<p><strong>Step 5: Technical Audit<\/strong><\/p>\n\n\n\n<p>Technical auditing constitutes the final phase of quality control and scientific rigor assurance prior to the public disclosure of data.<\/p>\n\n\n\n<p>In this stage, the coordinating analysts for each region (Amazon, Andes, Caribbean, Pacific, and Orinoco) conduct exhaustive supervision of each event to ensure the consistency and reliability of the evidence.&nbsp;<\/p>\n\n\n\n<p>The audit process focuses on three critical verifications:<\/p>\n\n\n\n<ol>\n<li>Satellite Evidence Quality: It is validated that the \"before\" and \"after\" images from the PlanetScope constellation are free of interference (clouds, shadows, or processing errors) that might prevent a clear interpretation of the event.<\/li>\n\n\n\n<li>Spatial Refinement Verification: Verification that the refined polygon faithfully represents the transformed area, ensuring that no deforested sectors have been omitted and that no areas of conserved natural vegetation or secondary vegetation have been included.<\/li>\n\n\n\n<li>Pressure Vector Coherence: It is evaluated whether the pressure vector adequately represents the assigned probable cause (e.g., livestock, mining, or natural causes), ensuring it is consistent with the territorial context and the visual patterns observed in high-resolution imagery.<\/li>\n<\/ol>\n\n\n\n<p><strong>Step 6: Publication and Generation of Technical Evidence (Reports)&nbsp;<\/strong><\/p>\n\n\n\n<p>Validated polygons of deforestation and natural vegetation loss that have successfully passed the validation, refinement, and technical audit phases are published weekly on the MapBiomas Alerta web platform.<\/p>\n\n\n\n<p>This stage represents the democratization of data, transforming technical analysis into an active transparency tool for immediate decision-making.<\/p>\n\n\n\n<p>For each confirmed event, the system automatically generates a detailed individual report (Alert Report), which consolidates the scientific evidence necessary for oversight, legal proceedings, or due diligence processes.<\/p>\n\n\n\n<p><strong>Each report contains the following data structure:<\/strong><\/p>\n\n\n\n<ul>\n<li><strong>Identification and Traceability: <\/strong>A unique alert code, consisting of an unrepeatable alphanumeric identifier, functions as the \"primary key\" for tracking the event.<\/li>\n\n\n\n<li><strong>Original Detection Source: <\/strong>Credit to the satellite system that generated the alert (IDEAM-SMByC, GLAD, RADD, among others).<\/li>\n\n\n\n<li><strong>Metrics and Geographical Context: <\/strong>Administrative and political localization, including details of the region, Department, and Municipality or Indigenous Territorial Entity (ETI) where the event is located.<\/li>\n\n\n\n<li><strong>Total Affected Area: <\/strong>The exact extent of the natural vegetation removed, expressed in hectares (ha).<\/li>\n\n\n\n<li><strong>High-Resolution Satellite Evidence: <\/strong>The system provides imagery from the PlanetScope constellation (3-meter resolution) with the exact dates of the \"before\" (intact natural vegetation cover) and \"after\" (transformed area) states, enabling irrefutable visual verification of the event.<\/li>\n\n\n\n<li><strong>Historical Analysis and Trajectories: <\/strong>The system provides a detailed history of the natural cover within the validated polygon, based on the MapBiomas Colombia land cover and land use time series and historical Landsat imagery mosaics. This analysis allows for the precise contextualization of the affected ecosystem's nature, determining whether the loss event corresponds to primary forest, savannas, flooded areas, or secondary vegetation. By evaluating the area's trajectory over time, it is possible to differentiate between recent transformations and long-term degradation processes, offering an essential technical perspective for understanding the ecological significance and the prior state of the intervened territory.<\/li>\n\n\n\n<li><strong>Overlay with Environmental Determinants and Land Use Planning: <\/strong>Automatic territorial intersections involve spatially overlaying the event with official layers to determine if the impact occurs in critical areas for land use planning, such as:\n<ul>\n<li>Forest Reserve Zones (Law 2 of 1959)<\/li>\n\n\n\n<li>National Natural Parks (PNN).<\/li>\n\n\n\n<li>Indigenous Reserves and Ethnic Territories.<\/li>\n\n\n\n<li>Environmental Protection Zones.<\/li>\n\n\n\n<li>Peasant Reserve Zones.&nbsp;<\/li>\n\n\n\n<li>Jurisdictions of the Corporaciones Aut\u00f3nomas Regionales (CAR).<\/li>\n\n\n\n<li>Rural Cadastre.<\/li>\n\n\n\n<li>Environmental Licenses.&nbsp;<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p>All of these reports are publicly and freely available in interoperable formats (PDF for reports and Shapefile for geospatial data), ensuring that technical evidence is directly actionable by any stakeholder in society.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Cancellation and Rectification of Post-Publication Alerts&nbsp;<\/strong><\/h4>\n\n\n\n<p>In certain situations, alerts published on the MapBiomas Alerta Platform may be rectified or even canceled, provided there is a formal notification or a well-founded request indicating potential errors associated with the alerts\u2014whether submitted by environmental authorities or platform users. In such cases, the technical team conducts a thorough analysis of the alerts.<\/p>\n\n\n\n<p>This analysis is performed by verifying Planet imagery, but may also include other complementary information sources if necessary, such as imagery from other satellites (Sentinel, Landsat, etc.), high-resolution satellite imagery available on Google Earth, and the \"MapBiomas Colombia Annual Land Cover and Use Mapping.\" In cases where it is confirmed that the published alert does not constitute a deforestation event or a loss of natural vegetation cover (regardless of legality or responsibility), the alert is canceled. This means it is removed from the map and platform statistics but remains in the database solely for individual lookup via its identification code.&nbsp;&nbsp;<\/p>\n\n\n\n<p>In some instances, rectifications to the spatial delimitation of the alert may be made to more accurately represent the reported event (Figure 3). Similarly, if an error or issue is associated with the images linked to the alert polygon, new images can be selected and updated on the platform. All rectifications are recorded in the system, and the information is made publicly available on the platform, including the date on which the alert was rectified.&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" loading=\"lazy\" width=\"812\" height=\"863\" src=\"https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/rectificacioningles.png\" alt=\"\" class=\"wp-image-288\" srcset=\"https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/rectificacioningles.png 825w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/rectificacioningles-287x300.png 287w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/rectificacioningles-768x802.png 768w, https:\/\/colombia.alerta.mapbiomas.org\/wp-content\/uploads\/sites\/20\/2026\/04\/rectificacioningles-11x12.png 11w\" sizes=\"(max-width: 812px) 100vw, 812px\" \/><\/figure>\n\n\n\n<p>Figure 3. Example of spatial boundary rectification of the alert after publication for alert ID 40219356, detected in 2025. Corrected due to secondary vegetation.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td>MapBiomas Alerta does not perform any analysis or reach any conclusions regarding the legality of the deforestation or natural vegetation cover loss alerts presented on the platform; every instance of detected and validated loss of natural vegetation generates an alert, a report, and a polygon. The evaluation of these matters is the exclusive responsibility of users, public agencies, or private and financial institutions that have free access to the open data provided by MapBiomas Alerta Colombia. MapBiomas is not responsible for the decisions made by these agencies and institutions based on the published alerts, as these represent impartial and verifiable data regarding the existence of deforestation and loss of natural vegetation.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><strong>LIMITATIONS OF THE METHOD<\/strong><\/p>\n\n\n\n<p>As every method, MapBiomas Alerta has some limitations that must be considered when applying its data:<\/p>\n\n\n\n<ol>\n<li><strong>Processing time:<\/strong> The ingestion of alerts from detection systems is carried out on a monthly basis, with the exception of IDEAM's SMByC, which publishes its early deforestation alerts quarterly.<\/li>\n<\/ol>\n\n\n\n<p>Since part of the alert processing is performed individually and visually by trained analysts, the validation and processing time depends on the region (Amazon, Andes, Caribbean, Pacific, and Orinoqu\u00eda) and the time of year. Therefore, the period between the detection date by the source system and the publication on the MapBiomas Alerta Colombia platform may range from 30 to 90 days.<\/p>\n\n\n\n<p>The focus of MapBiomas Alerta is to increase the certainty and associated information regarding reported deforestation and vegetation cover loss events, and to provide detailed, ready-to-use reports that complement current detection systems.<\/p>\n\n\n\n<ol start=\"2\">\n<li><strong>Alert omissions:<\/strong> the deforestation alerts in MapBiomas Alerta are validated and refined only if they have been previously captured by an external detection system. This means that any omissions by those systems directly affect the results evaluated and presented on the platform.<\/li>\n<\/ol>\n\n\n\n<p>In Colombia, there are official systems such as SMByC from IDEAM, as well as global sources like GLAD, RADD, JJ-FAST, or LUCA, which together cover the entire national territory. GLAD-L uses Landsat imagery (30 m) to automatically identify forest cover disturbances in tropical regions. Its performance is most reliable in areas with dense forest cover (&gt;60%), such as the Amazon, but it may face limitations in detecting changes in fragmented landscapes or those with mixed cover, such as the dry Caribbean or the Orinoqu\u00eda savannas.<\/p>\n\n\n\n<p>This means that, although the systems cover the entire country, omissions may occur in detecting the loss of non-forest vegetation covers, as global algorithms are not always calibrated to the specific characteristics of each Colombian ecosystem. The use of multiple sources for the same region aims to reduce these omissions.<\/p>\n\n\n\n<ol start=\"3\">\n<li><strong>Underestimation of the deforestation or vegetation loss rate:<\/strong> when validating and refining an alert, a pair of high-resolution PlanetScope satellite images is selected to clearly represent the before and after of the vegetation loss event. The \u201cbefore\u201d image corresponds to the most recent one available within a period of up to 12 months prior to detection (except in exceptional cases due to image availability), while the \u201cafter\u201d image is the one closest to the end of the vegetation loss event.<\/li>\n<\/ol>\n\n\n\n<p>In regions with high cloud cover, such as the Andes and the Colombian Pacific, the availability of cloud-free images may delay the acquisition of comparative imagery, extending the time interval between both captures by days, weeks, or even months.<\/p>\n\n\n\n<p>While this does not change the fact that the deforestation and\/or loss of natural vegetation cover occurred between those two dates, it does impact the estimation of the average speed of the loss event, which tends to be underestimated in the platform's reports.<\/p>\n\n\n\n<ol start=\"4\">\n<li><strong>Automatic polygon delineation:<\/strong> The polygons that outline the refined alerts in Colombia are generated through an automatic classification process that identifies the area of change between the \u201cbefore\u201d and \u201cafter\u201d images \u2014 that is, the zone where native vegetation was removed.<\/li>\n<\/ol>\n\n\n\n<p>During this delineation, sectors showing signs of prior transformations or small patches of trees remaining within the deforested area are excluded. The delineation processing in MapBiomas Alerta Colombia includes cleaning tools to reduce the presence of tiny polygons or small islands within the refined polygons, as well as simplification procedures to remove excess vertices that make the final geometry more complex.<\/p>\n\n\n\n<p>In the Colombian context, this limitation is particularly relevant in areas where deforestation occurs in irregular and small-scale patterns, such as Amazonian Indigenous chagras, artisanal mining in the Pacific region, or itinerant grazing in the Orinoqu\u00eda, which often leave scattered vegetation remnants and poorly defined edges. These situations may result in polygons that are less accurate compared to the actual shape of the deforestation event.&nbsp;<\/p>\n\n\n\n<ol start=\"5\">\n<li><strong>Limitations regarding non-forest natural vegetation:<\/strong> In Colombia, detecting the loss of non-forest vegetation such as natural grasslands, savannas, or herbaceous wetlands presents challenges, since the alert systems used (GLAD, RADD, JJ-FAST, SMByC, etc.) were primarily designed to identify forest loss.<\/li>\n<\/ol>\n\n\n\n<p>This means that transformation processes affecting key ecosystems in the country \u2014 such as the Orinoqu\u00eda savannas or the Andean p\u00e1ramos \u2014 tend to be underrepresented in reports. Nevertheless, the use of high-resolution imagery from the PlanetScope constellation occasionally allows the identification of losses in these non-forest vegetation covers, provided they occur within or around an area with a confirmed issued alert. Therefore, current detection systems still underestimate the loss of non-forest native vegetation. To increase the likelihood of detecting these events, Fundaci\u00f3n Gaia Amazonas issues specialized alerts for native vegetation loss in the Orinoqu\u00eda region and in Colombian p\u00e1ramos.&nbsp;<\/p>\n\n\n\n<p><strong>Technical and Dynamic Nature of the MapBiomas Alerta System<\/strong><\/p>\n\n\n\n<p>MapBiomas Alerta Colombia operates as a specialized system for the validation and spatial refinement of natural vegetation loss events previously detected by alert systems. Unlike automated batch detection systems, the methodology is based on an individualized analysis (event by event).<\/p>\n\n\n\n<p>This process involves expert visual validation supported by daily high-resolution imagery from the PlanetScope constellation (3 to 3.7 meters), allowing for the transformation of a preliminary detection into complementary evidence with greater spatial detail.<\/p>\n\n\n\n<p>Due to the rigor of this workflow\u2014which includes polygon refinement and technical audits\u2014the system is updated weekly, integrating alerts as they complete their verification cycle.<\/p>\n\n\n\n<p>Consequently, the data published for the current year should be considered dynamic and partial, reflecting the phased progress of validation across the national territory at the time of the query.<\/p>\n\n\n\n<p>The interval between the original satellite detection and the validated publication can range from 30 to 180 days, ensuring the elimination of false positives and the exact delimitation of the affected area.<\/p>\n\n\n\n<p>The final consolidation and the generation of aggregated statistics are formalized annually through the Annual Deforestation Report.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Usage Note: Any comparative exercise between these figures and other monitoring systems must be carried out within a framework of technical interoperability, considering variations in spatial resolutions, definitions of vegetation cover, and the minimum area thresholds reported by each platform.<\/strong><br><strong>The statistical information presented by the platform is partial and depends on the progress of alert validation. To consolidate data corresponding to a defined period or a specific territory, you must check the progress level and take into account the limitations and advantages of conducting such an exercise.<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>DIFFERENCES FROM THE OFFICIAL ANNUAL DATA&nbsp;<\/strong><\/h4>\n\n\n\n<p>MapBiomas Alerta is a system designed to monitor pre-existing, specific deforestation events. Updates are performed weekly with the alerts that the technical team manages to validate. The process is carried out through an individualized analysis of each event, rather than from data batches. The platform presents the consolidated data of the area evaluated at the time of the query, and progress can be verified through the statistics section of the platform. Once 100% of the validated alerts for a specific year are reached, the figures can be considered reliable for comparison with other reports from that same period. However, to make these comparisons, it is necessary to take into account the methodological differences, reporting criteria, and the accuracy of each system.&nbsp;<\/p>","protected":false},"excerpt":{"rendered":"<p>CONOZCA EL M\u00c9TODO DE MAPBIOMAS ALERTA MapBiomas Alerta es un sistema de validaci\u00f3n y publicaci\u00f3n que compila e integra alertas provenientes de diversas fuentes nacionales y globales de detecci\u00f3n de deforestaci\u00f3n y p\u00e9rdida de cobertura vegetal natural, basadas en t\u00e9cnicas de teledetecci\u00f3n e interpretaci\u00f3n asistida por computaci\u00f3n y clasificaci\u00f3n supervisada. Este conjunto de alertas se [&hellip;]<\/p>","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_uag_custom_page_level_css":""},"acf":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false,"trp-custom-language-flag":false,"infographic":false,"team":false},"uagb_author_info":{"display_name":"Rafael Coelho","author_link":"https:\/\/colombia.alerta.mapbiomas.org\/en\/author\/rafael-coelho\/"},"uagb_comment_info":0,"uagb_excerpt":"CONOZCA EL M\u00c9TODO DE MAPBIOMAS ALERTA MapBiomas Alerta es un sistema de validaci\u00f3n y publicaci\u00f3n que compila e integra alertas provenientes de diversas fuentes nacionales y globales de detecci\u00f3n de deforestaci\u00f3n y p\u00e9rdida de cobertura vegetal natural, basadas en t\u00e9cnicas de teledetecci\u00f3n e interpretaci\u00f3n asistida por computaci\u00f3n y clasificaci\u00f3n supervisada. Este conjunto de alertas se&hellip;","_links":{"self":[{"href":"https:\/\/colombia.alerta.mapbiomas.org\/en\/wp-json\/wp\/v2\/pages\/34"}],"collection":[{"href":"https:\/\/colombia.alerta.mapbiomas.org\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/colombia.alerta.mapbiomas.org\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/colombia.alerta.mapbiomas.org\/en\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/colombia.alerta.mapbiomas.org\/en\/wp-json\/wp\/v2\/comments?post=34"}],"version-history":[{"count":11,"href":"https:\/\/colombia.alerta.mapbiomas.org\/en\/wp-json\/wp\/v2\/pages\/34\/revisions"}],"predecessor-version":[{"id":321,"href":"https:\/\/colombia.alerta.mapbiomas.org\/en\/wp-json\/wp\/v2\/pages\/34\/revisions\/321"}],"wp:attachment":[{"href":"https:\/\/colombia.alerta.mapbiomas.org\/en\/wp-json\/wp\/v2\/media?parent=34"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}