UNOSAT Climate Service Flood and Drought Monitoring

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UNOSAT Climate Service Flood and Drought Monitoring El Niño

Colombia 24 March 2016 Geneva, Switzerland UNOSAT Contact:

org UNITAR UNOSAT, IEH T: +41 22 767 4020 (UNOSAT

1 UNOSAT Climate Service Flood and Drought Monitoring El Niño Monthly Update Colombia March 2016 El Niño Monthly Update Colombia 24 March 2016 Geneva, Switzerland UNOSAT Contact: Postal Address: UNITAR UNOSAT, IEH T: (UNOSAT Operations) Chemin des Anémones 11, 24/7 hotline: CH-1219, Genève, Suisse 1

Overview The El Niño-Southern Oscillation (ENSO) is a naturally occurring phenomenon that involves fluctuating ocean temperatures in the equatorial Pacific.

2 Overview The El Niño-Southern Oscillation (ENSO) is a naturally occurring phenomenon that involves fluctuating ocean temperatures in the equatorial Pacific. The pattern generally fluctuates between two states: warmer than normal central and eastern equatorial Pacific Sea Surface Temperatures SSTs (El Niño) and cooler than normal central and eastern equatorial Pacific SSTs (La Niña). During an El Niño, the trade winds weaken in the central and western Pacific and the clouds and rainstorms associated with warm ocean waters shift toward the east. The weather changes all over the planet due to the energy released into the atmosphere by the warm waters. According to IDEAM, many provinces of Colombia are in a state of emergency due to extreme drought, high temperatures and forest fires caused by the 2015 El Niño. During La Niña, the trade winds are unusually strong because of a raised pressure gradient between the eastern and western Pacific. As a result, upwelling is enhanced along the coast of South America, contributing to colder than normal surface waters over the eastern tropical Pacific and warmer than normal surface waters in the western tropical Pacific. In this context, UNOSAT is conveying this monthly update in order to support OCHA FD - UMAIC responding to its request for population exposure assessment to El Niño impacts, in particular to drought and rainfall anomalies. Drought 234,423 Square kilometres of potentially affected agricultural lands in La Guajira department (from Oct to Dec 2015) 3.13 Million people living within rural areas potentially affected by drought (departments)in February Potential active fires in January 2016 Rainfall Precipitation anomaly October January ,721,772 Population Exposure within areas covered with well below average rainfall. Flood Low probability 30% of probability of la Niña phenomenon in July 2016 No flood alert, flood forecast and planned satellite tasking In this report, we are picturing a rainfall outlook describing observations of 7-day estimated accumulated rainfall provided by NASA, 7 days rainfall forecast from NOAA in Colombia. Then, Rainfall anomalies based on IDEAM data from 01 October 2015 to 29 Feb 2016 are illustrated in maps and we report the population exposure per department (Colombia Admin Level 1). Subsequently, we reveal a flood forecast mainly related on ENSO status and forecast, from October 2015 to December 2016, presented in reference and IRI/CPC. Afterwards, we are conveying a drought monitoring based on changes in vegetation conditions measured by the Global MODIS vegetation index products provided by NASA USGS LP DAAC. Later, we assess the potential drought affected agricultural land and population exposure per department (Colombia Admin Level 1). At the end of the report, we are monitoring the number of potential fires based on NASA Active Fire Data. 2

3 Contents 1 Climate Outlook Flood Monitoring Drought Monitoring

1 Climate Outlook No significant values of accumulated precipitation have been registered in the past 7 days. Moderate rain is forecast for the next 14 days.

Atlántico, Córdoba, Bolivar, Sucre and Chocó (from Jan to Mar 2016) 8,721,772 Population Exposure within areas covered with significant rainfall anomalies

NIC ECU COL VEN BRA According to TRMM satellite based precipitation estimates, moderate values of accumulated precipitation have been registered in the

4 1 Climate Outlook No significant values of accumulated precipitation have been registered in the past 7 days. Moderate rain is forecast for the next 14 days. Rainfall anomalies for the period between October 2015 and March 2016, especially well below average precipitation in Atlántico, La Guajira, Sucre, Bolivar and Córdoba. Satellite based observations derived from TRMM data (Source: NASA), 2 week Regionalized NCEP GFS Products (Source: NOAA) and rainfall anomalies retrieved from IDEAM archive. Precipitation anomaly Well below average precipitation in La Guajira, Boyacá, Cundinamarca, Huila and Caldas (from Oct to Dec 2015) and in La Guajira, Atlántico, Córdoba, Bolivar, Sucre and Chocó (from Jan to Mar 2016) 8,721,772 Population Exposure within areas covered with significant rainfall anomalies from October 2015 to February day Estimated Accumulated Rainfall Time Period: 18 March March NIC ECU COL VEN BRA According to TRMM satellite based precipitation estimates, moderate values of accumulated precipitation have been registered in the Southeastern part of Colombia in the past 7 days. (Source: NASA). PER Precipitation Forecast Time Period: 24 March April 2016 Low Moderate High NIC COL VEN More rain is forecast for the next 14 days in Colombia especially in the Eastern and Southern parts of the country. (Source: NOAA). ECU PER BRA Based on observed precipitation over past 7days and provided forecast for Colombia, there is a low concern for the next 2 weeks around flood prone areas in Southern Amazonas and Nariño districts. 4

5 Rainfall anomalies Time Period : 01 October Feb 2016 Analysis: The maps below illustrate monthly rainfall anomalies over Colombia for October, November and December 2015 and for January and February This analysis is based on estimations realised by the Instituto de Hidrología, Meteorología y Estudios Ambientales de Colombia (IDEAM) and accessed via Unidad de Manejo y Análisis de Información Colombia (UMAIC). Results: The maps show that significant below average values have been mainly observed in December 2015, January 2016 and February

6 Population exposure Time Period : 01 October March 2016 Analysis: According to significant values of below and above rainfall conditions for January 2016, below is reported population exposure per department (Colombia Admin Level 1) for the two periods Oct Dec 2015 and Jan Mar Population estimates are based on census data for Colombia accessed via Unidad de Manejo y Análisis de Información Colombia (UMAIC). Results: In terms of percentage of population exposure to extreme values of rainfall anomalies, most affected departments in Colombia are: Atlántico (86.9%), La Guajira (79.7%), Sucre (79.6%), Bolivar (71.9%) and Córdoba (68.6%) between October and December 2016 and Sucre (81.7%), La Guajira (80.7%), Atlántico (76.2%), Bolivar (75.1%) and Córdoba (69.5%) for the first trimester of Department Population exposure to rainfall anomalies Oct 2015 Dec 2015 Jan 2016 Mar 2016 Well below average Well above average Well below average Well above average Amazonas Antioquia 432, ,579 Arauca 75, ,241 8 Archipiélago de San Andrés Atlántico 2,114, ,853,799 Bogotá D.C. 467,028 9, ,136 Bolívar 1,489, ,557,787 Boyacá 73, ,285 Caldas 18,675 19,483 Caquetá Casanare Cauca 166, ,003 Cesar 189, ,545 Chocó 149, ,122 Córdoba 1,155,487 1,170,226 Cundinamarca 513, ,475 Guainia Guaviare Huila 993 1,246 La Guajira 739,806 1, ,284 Magdalena 231,938 5, ,306 Meta 532 2, ,164 Nariño 49,728 52,179 Norte de Santander 203, ,437 Putumayo Quindio 24 Risaralda Santander 92, ,555 Sucre 670, ,782 Tolima 30,150 29,629 Valle del Cauca 47,911 49,425 Vaupes Vichada Grand total 8,915,344 20,335 8,504,375 3,489 Table 1 - Population exposure on a department level within areas affected by rainfall anomalies of well below (< 40) and well above average values (> 160). This analysis refers for two different trimesters: the first one considers average IDEAM anomalies between October 2015 and December 2015 and the second one the IDEAM rainfall anomaly conditions first trimester of 2016 assuming a strong El Niño conditions (January to March 2016). This is not a direct indicator of affected population by rainfall, rather an estimate on number of people living in the areas with extreme rainfall anomalies. 6

2 Flood Monitoring No major flooding have been reported in the country. No alert from short term flood forecast from global hydrological model reports.

Time Period: 01 March 2016 31 December 2016 Flood Forecast 30% of probability of la Niña phenomenon in July 2016 From late 2010 until late 2011, more than half of Colombia s

La Niña affected 4 million people and caused huge economic losses mainly related to destruction of infrastructure and flooding agricultural lands.

Based on past events and on forecast models, the same agency is also predicting, (with 50% probability) that La Niña will start by fall 2016.

Figure 1 - ENSO status and forecast (IDEAM, 2016) The International Research Institute (IRI) of Climate and Society together with Climate Prediction Centre (CPC) of NOAA also

7 2 Flood Monitoring No major flooding have been reported in the country. No alert from short term flood forecast from global hydrological model reports. ENSO status and forecast are provided by NOAA, IDEAM and IRI based on forecast models. Low alert No significant Rainfall, no flood alert. Time Period: 01 March December 2016 Flood Forecast 30% of probability of la Niña phenomenon in July 2016 From late 2010 until late 2011, more than half of Colombia s territory was affected by the severe rains and flooding associated with La Niña phenomenon which was the strongest climatic event in 40 years. La Niña affected 4 million people and caused huge economic losses mainly related to destruction of infrastructure and flooding agricultural lands. According to NOAA, El Niño has started to decline with decreasing SSTs anomalies across most of the equatorial Pacific. Based on past events and on forecast models, the same agency is also predicting, (with 50% probability) that La Niña will start by fall The figure 1 below, published by IDEAM, summarising the ENSO status and forecast as of March Figure 1 - ENSO status and forecast (IDEAM, 2016) The International Research Institute (IRI) of Climate and Society together with Climate Prediction Centre (CPC) of NOAA also published a probabilistic forecast of ENSO phenomenon in 2016 described by the diagram in the figure below. Figure 2 - IRI/CPC Model-Based Probabilistic ENSO Forecast as of 17 March 2016 (IRI/CPC, 2016) A shown in the figure 2, starting from June, La Niña gets more and more likely to happen reaching over 50% probability by fall The intensity of La Niña is still unknown but usually, this phenomenon manifests in Colombia as torrential rainfall with possibility of floods. 7

8 3 Drought Monitoring Significant dry conditions over the Amazonia region in February MODIS active fires data show an intense fire activity during January La Guajira is the most drought affected department in terms of population and agricultural land exposure. Exposure estimates of population and agricultural land based on Normalized Differential Vegetation Index (NDVI) anomalies from MODIS data (Source: NASA/GSFC/GIMMS) 234,423 Square kilometres of potentially affected agricultural lands in La Guajira department (from Oct to Dec 2015) Changes in vegetation conditions Time Period: 01 October February Million people living within rural areas potentially affected by drought (departments) in February 2016 Analysis: The Normalized Difference Vegetation Index (NDVI) is an index of photosynthetic activity greenness, and is the most commonly used vegetation index. NDVI Anomaly indicates the areas with above or below normal vegetation conditions for a specific period when compared to a 15 year average of the same time period ( ). NDVI anomaly is generally used as an indicator for drought related conditions, especially on vegetation. Vegetation indices data are acquired from Terra and Aqua (MODIS) at 250 m resolution. Results: The maps below illustrate monthly vegetation conditions over Colombia by analysing the vegetation changes (NDVI anomaly) for the period between October 2015 and February From an overall prospective, areas in Caribbean, Central Andes, North East Andes and Amazonia regions have shown significant changes in vegetation conditions (below normal values, almost dry). Most affected areas have been detected in Caldas, Caquetá, Putumayo and Huila departments. Significant dry conditions over the Amazonia region in February are probable based on the well below average precipitation figures observed in January. The pacific region has shown mostly above normal values over this period. 8

9 Potential drought affected agricultural land and population exposure Time Period: 01 October February 2016 Analysis: Potentially affected agricultural land and population exposure per Department (Colombia Admin Level 1) under below normal vegetation conditions. Population estimates are based on census data for Colombia accessed via Unidad de Manejo y Análisis de Información Colombia (UMAIC). Agricultural areas are identified using global land cover data from ESA (2009). Results: In tables 2 and 3 are reported values of population and agricultural land exposure to potential drought conditions. Significant figures are highlighted. Department Population exposure to potential drought conditions over rural areas Oct 2015 Nov 2015 Dec 2015 Jan 2016 Feb 2016 Amazonas 9,323 8,411 10,025 2,633 17,859 Antioquia 218, ,801 66, , ,712 Arauca 13,472 16,835 6,648 7,247 15,796 Archipiélago de San Andrés 1, , Atlántico 23,390 16,896 40,895 56,069 44,008 Bogotá D.C. 3,863 6, ,079 1,616 Bolívar 48,618 58,577 61, , ,960 Boyacá 154, ,519 51, , ,446 Caldas 87,280 57,919 4,211 33,752 58,702 Caquetá 33,118 27,499 16,534 21,283 90,722 Casanare 7,552 12,320 3,143 4,163 6,710 Cauca 322, ,680 32, , ,384 Cesar 48,085 32,439 47,862 66,245 66,429 Chocó 118,274 52,414 41,382 77, ,035 Córdoba 120,945 92,839 34, , ,175 Cundinamarca 198, ,261 63, , ,341 Guainía 2,119 3,396 1, ,596 Guaviare 7,206 5,031 3, ,494 Huila 246, ,804 98, , ,922 La Guajira 246, , , , ,967 Magdalena 46,882 43,842 88, , ,581 Meta 20,154 32,933 13,064 18,699 48,996 Nariño 326, , ,739 84, ,986 Norte de Santander 51,559 76,222 18,132 36,336 62,678 Putumayo 17,275 20,346 20,655 34, ,622 Quindio 18,043 13,244 2,282 3,662 10,590 Risaralda 77,659 52,348 8,129 23,304 36,074 Santander 78,283 99,722 24,743 56,544 78,821 Sucre 26,742 24,682 20,254 66,676 49,064 Tolima 93,241 99,971 21, , ,173 Valle del Cauca 226, ,201 44, , ,112 Vaupes 3,170 5,072 4, ,203 Vichada 4,942 4,323 2, ,139 Grand total 2,904,324 2,547,129 1,231,592 2,491,596 3,132,426 Table 2 - Population exposure to potential drought on a department level (people living within the rural areas covered with vegetation conditions below average value). Highlighted in orange are values of affected population in rural areas above 25% of total departmental population. This is not a direct indicator of drought affected population, rather an estimate on number of people living in the areas with drier vegetation conditions. 9

10 Department Agricultural land exposure to potential drought conditions (sqkm) Oct 2015 Nov 2015 Dec 2015 Jan 2016 Feb 2016 Amazonas Antioquia 2,631 1,782 1,076 2,270 4,004 Arauca Archipiélago de San Andrés Atlántico Bogotá D.C Bolívar ,713 3,034 Boyacá 760 1, ,037 Caldas Caquetá 1,177 1, ,036 4,040 Casanare 1,190 1, ,347 Cauca 3,373 1, ,261 1,778 Cesar 2,928 1,385 3,464 4,625 4,070 Chocó 2,439 1, ,042 2,168 Córdoba 1,689 1, ,962 2,629 Cundinamarca 1,085 2, ,784 1,941 Guainía Guaviare Huila 4,684 2,720 1,843 3,588 2,808 La Guajira 4,676 4,258 5,092 4,729 4,043 Magdalena 2,135 1,781 5,056 7,059 5,668 Meta 1,298 1,787 1,056 1,011 2,780 Nariño 2,976 1, ,602 Norte de Santander ,131 Putumayo ,341 Quindio Risaralda Santander 997 1, ,374 Sucre , Tolima 1,952 1, ,429 1,814 Valle del Cauca 3,113 1, ,723 2,097 Vaupes Vichada Grand total 44,962 35,529 27,450 45,600 57,025 Table 3 - Potential drought affected agricultural land on a department level (agricultural land within the area covered with vegetation conditions below average value). This is not a direct indicator of drought affected agricultural land, rather an estimate on square kilometres of agricultural land in the areas with drier vegetation conditions 10

Potential fires affected departments Time Period: 01 October 2015 29 February 2016 Analysis: Potentially fires affected Departments (Colombia Admin Level 1).

11 Potential fires affected departments Time Period: 01 October February 2016 Analysis: Potentially fires affected Departments (Colombia Admin Level 1). Results: The map below shows satellite-detected Active fires, collected by the NASA Moderate Resolution Imaging Spectroradiometer and accessed via NASA FIRMS, from 1 October February This analysis is based only on high-confidence data detected by MODIS. From an overall prospective, areas located into Orinoquìa, Central Caribbean Coast, North-western Amazonia and North East Andes regions result to be more affected by potential fires. Orinoquìa region has been continuously interested by potential fire activities between October 2015 and February On February 2016 a sensitively increase of fire detected fires have registered in Caribbean lowlands areas. 11

The graph 1 represents a complete history of MODIS fire detections for Colombia which were summarized by a daily total fire detections since June 2001.

Numbers of fires acquired in early 2007 show the largest event recorded by MODIS in Colombia over the past 15 years.

12 The graph 1 represents a complete history of MODIS fire detections for Colombia which were summarized by a daily total fire detections since June Historical fire detection analysis indicates that recent fires in Colombia are almost intense as past 2 years. Numbers of fires acquired in early 2007 show the largest event recorded by MODIS in Colombia over the past 15 years. Graph 1: Historical MODIS fire detection(active Fires) for Colombia as of 29 February 2016 Peak of occurrence of fire has been observed during the month of January 2016 (see Graph 2). Graph 2: MODIS fire detection (Active Fires) for Colombia from 1st of October 2016 to 29 February 2016 The number of active fires occurred in January is in line with well below average values shown into IDEAM rainfall anomalies for the month of January. 12

13 Significant values of active fires have been detected in January 2016 over Meta, Vichada, Caquetá and Casanare departments. MODIS fire detections have been decreased in February 2016, however a sensitively increase have been registered in the northern part of the country particularly for Bolívar, Arauca and Magdalena departments. Department Oct 2015 Nov 2015 Active fires Dec 2015 Jan 2016 Amazonas Antioquia Arauca Archipiélago de San Andrés, Providencia y Santa Catalina Atlántico Bogotá D.C Bolívar Boyacá Caldas Caquetá Casanare Cauca Cesar Chocó Córdoba Cundinamarca Guainía Guaviare Huila La Guajira Magdalena Meta Nariño Norte de Santander Putumayo Quindio Risaralda Santander Sucre Tolima Valle del Cauca Vaupes Vichada Feb 2016 Grand total Table 4 - Potential fire affected departments in Colombia for the period between 1st of October 2015 and 29 of January This is not a direct indicator of drought affected areas, rather an estimate of potential fire activities in the country 13

Sources indicate flood and rainfall observation data and forecast, satellite based analysis, news, official alerts and weather bulletins providers.

14 Sources indicate flood and rainfall observation data and forecast, satellite based analysis, news, official alerts and weather bulletins providers. Some of the products referenced in this summary are based on best available models and satellite based observations and may not be validated in the field prior to release. It is important to note the presence of limitations in these data sources and that flood awareness included into this overview should be treated with caution. This document is part of an ongoing flood awareness project of UNITAR/UNOSAT (Flood-FINDER, a Forecastbased Integrated Detection System for Emergency Response and Disaster Risk Reduction, info at: in support of international humanitarian assistance and created to respond to the needs of UN agencies and their partners. UNOSAT Contact: Postal Address: unosat@unitar.org UNITAR UNOSAT, IEH T: (UNOSAT Operations) Chemin des Anémones 11, 24/7 hotline: CH-1219, Genève, Suisse Submit geotag photos via our UN-ASIGN app for smartphones. 14

This map illustrates precipitation anomalies, estimated by the Instituto de Hidrología, Meteorología y Estudios Ambientales de Colombia (IDEAM) and accessed via Unidad de Manejo y

With the aim of understanding more about the effects of the El Nino event in Colombia, the goal of this analysis is to provide a snapshot about the monthly evolution of precipitation

Analysis with data collected by IDEAM, accessed via Unidad de Manejo y Análisis de Información Colombia (UMAIC) OCTOBER 2015 NOVEMBER 2015 Version 1.

October 2015-29 February 2016 Well below average (<40) Moderately below average (40-80) Normal (80-120) Moderately above average (120-160) Well above average (>160) JANUARY 2016 I

Other Data: USGS, UNCS, NASA, NGA Analysis : UNITAR / UNOSAT Production: UNITAR / UNOSAT Analysis conducted with ArcGIS v10.

here are not warranted to be error-free nor do they imply official endorsement or acceptance by the United Nations.

15 This map illustrates precipitation anomalies, estimated by the Instituto de Hidrología, Meteorología y Estudios Ambientales de Colombia (IDEAM) and accessed via Unidad de Manejo y Análisis de Información Colombia (UMAIC), from 1 October February With the aim of understanding more about the effects of the El Nino event in Colombia, the goal of this analysis is to provide a snapshot about the monthly evolution of precipitation anomaly between October 2015 and February This is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT. Analysis with data collected by IDEAM, accessed via Unidad de Manejo y Análisis de Información Colombia (UMAIC) OCTOBER 2015 NOVEMBER 2015 Version Activation Number: TBD N o u a k c ho t t Production Date: 3/21/2016 DECEMBER 2015 Drought F Map Extent LEGEND Capital International Boundary Precipitation anomaly between 1 October February 2016 Well below average (<40) Moderately below average (40-80) Normal (80-120) Moderately above average ( ) Well above average (>160) JANUARY 2016 I FEBRUARY 2016 Km Map Scale for A3: 1:17,000,000 Precipitation Data: IDEAM Dates: Oct Feb 2016 Copyright: IDEAM Road Data : Google Map Maker / OSM / ESRI Other Data: USGS, UNCS, NASA, NGA Analysis : UNITAR / UNOSAT Production: UNITAR / UNOSAT Analysis conducted with ArcGIS v10.2 Coordinate System: WGS 1984 UTM Zone 18N Projection: Transverse Mercator Datum: WGS 1984 Units: Meter The depiction and use of boundaries, geographic names and related data shown here are not warranted to be error-free nor do they imply official endorsement or acceptance by the United Nations. UNOSAT is a program of the United Nations Institute for Training and Research (UNITAR), providing satellite imagery and related geographic information, research and analysis to UN humanitarian and development agencies and their implementing partners. This work by UNITAR/UNOSAT is licensed under a Creative Commons Attribution-NonCommercialShareAlike 3.0 Unported License. Co nta c t Infor m a t ion: unos a t@ u nita r.or g 24 /7 H ot line : nita r.or g/un os at

Th is m a p provide a n e stim a tion of ch a ng e s in ve g e ta tion condition a t countryle ve l b a se don NASA s MODI S da ta.

anom a lie s re fe r to sa te llite b a se d ob se rva tions from 20012015 da ta.

droug h t conditions. Th is is a pre lim ina ry a na lysis & h a s not ye t b e e n va lida te din th e fie ld.p le a se se ndg roundfe e db a ck to UNI TAR /UNOSAT.

16 Th is m a p provide a n e stim a tion of ch a ng e s in ve g e ta tion condition a t countryle ve l b a se don NASA s MODI S da ta.th e Norm a lize d Diffe re nce Ve g e ta tion I nde x( NDVI )is a n inde xof ph otosynth e tica ctivity g re e nne ss, a nd is th e m ost com m only use d ve g e ta tion indice s.anom a lie s re fe r to sa te llite b a se d ob se rva tions from da ta.i t is to b e note d th a t NDVIa nom a lyis not a dire ct re pre se nta tion of droug h t b ut a n inde xth a t indica te s th e ve g e ta tion va ria tion wh ich could b e th e re sult of e xisting droug h t conditions. Th is is a pre lim ina ry a na lysis & h a s not ye t b e e n va lida te din th e fie ld.p le a se se ndg roundfe e db a ck to UNI TAR /UNOSAT. Analysis with MODIS data acquired October, November, December 2011 to 2014 and 2015, January and February 2001 to 2015 and 2016 OCTOBER 2015 NOVEMBER Activa tion Num b e r: TBD N o u a k c ho t t Ve rsion 1. 0 DECEMBER 2015 P roduction Da te : 3/ 23/ 2016 Drought F Map Extent LEGEND Capital International Boundary NDVI anomaly 1 October February 2016 Above Normal Normal JANUARY 2016 I FEBRUARY 2016 Below Normal (most dry) Map Scale for A3: 1:17,000, Km 500 Sa te llite Da ta :MODI S Re soultion:250m Copyrig h t:nasa Source :GI MMS( NASAGSFC)a ndglam ( USDA) Roa dda ta :Goog le Ma pma ke r /OSM /ESRI Oth e r Da ta :USGS,UNCS,NASA,NGA Ana lysis :UNI TAR/UNOSAT P roduction:uni TAR/UNOSAT Ana lysis conducte dwith ArcGI Sv10. 2 Coordina te Syste m :W GS1984UTM Zone 18N P roje ction:tra nsve rse Me rca tor Da tum :W GS1984 Units:Me te r Th e de piction a nd use of b ounda rie s, g e og ra ph ic na m e s a ndre la te dda ta sh own h e re a re not wa rra nte d to b e e rrorfre e nor do th e yim plyofficia l e ndorse m e nt or a cce pta nce b y th e Unite d Na tions.unosat is a prog ra m of th e Unite dna tions I nstitute for Tra ining a nd Re se a rch ( UNI TAR),providing sa te llite im a g e ry a nd re la te d g e og ra ph icinform a tion,re se a rch a nd a na lysis to UN h um a nita ria n a nd de ve lopm e nt a g e ncie s a nd th e ir im ple m e nting pa rtne rs. Th is work b y UNI TAR/ UNOSAT is lice nse d unde r a Cre a tive Com m ons Attrib utionnoncom m e rcia lsh a re Alike 3. 0Unporte dlice nse. Co nta c t Infor m a t ion: unos a t@ u nita r.or g 24 /7 H ot line : nita r.or g/un os at

This map illustrates satellite-detected Active fires, collected by the NASA Moderate Resolution Imaging Spectroradiometer and accessed via NASA FIRMS, from 1 October 2015-29 February 2016.

The graph represents a complete history of MODIS fire detections for Colombia which were summarized by a daily total fire detections since June 2001.

Numbers of fires acquired in early 2007 show the largest event recorded by MODIS in Colombia over the past 15 years.this is a preliminary analysis & has not yet been validated in the field.

Analysis with data collected by the NASA Moderate Resolution Imaging Spectroradiometer, accessed via NASA FIRMS OCTOBER 2015 NOVEMBER 2015 Activation Number: TBD N o u a k c ho t t Version 1.

2015-29 February 2016 JANUARY 2016 FEBRUARY 2016 HISTORICAL MODIS FIRE DETECTION AS OF 29 FEB 2016 I Map Scale for A3: 1:17,000,000 0 50 100 200 300 400 Km 500 Road Data : Google Map Maker /

2 Coordinate System: WGS 1984 UTM Zone 18N Projection: Transverse Mercator Datum: WGS 1984 Units: Meter MODIS FIRE DETECTION: 1 OCT 2016-29 FEB 2016 The depiction and use of boundaries,

17 This map illustrates satellite-detected Active fires, collected by the NASA Moderate Resolution Imaging Spectroradiometer and accessed via NASA FIRMS, from 1 October February This analysis is based only on high-confidence data detected by MODIS. The graph represents a complete history of MODIS fire detections for Colombia which were summarized by a daily total fire detections since June Historical fire detection analysis indicates that recent fires in Colombia are almost intense as past 2 years. Numbers of fires acquired in early 2007 show the largest event recorded by MODIS in Colombia over the past 15 years.this is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT. Analysis with data collected by the NASA Moderate Resolution Imaging Spectroradiometer, accessed via NASA FIRMS OCTOBER 2015 NOVEMBER 2015 Activation Number: TBD N o u a k c ho t t Version 1.0 DECEMBER 2015 Production Date: 3/21/2016 Wild Fires F Map Extent LEGEND Capital ( Occurence of Fire International Boundary Relative spatial density of Fire Occurences between 1 October February 2016 JANUARY 2016 FEBRUARY 2016 HISTORICAL MODIS FIRE DETECTION AS OF 29 FEB 2016 I Map Scale for A3: 1:17,000, Km 500 Road Data : Google Map Maker / OSM / ESRI Other Data: USGS, UNCS, NASA, NGA Analysis : UNITAR / UNOSAT Production: UNITAR / UNOSAT Analysis conducted with ArcGIS v10.2 Coordinate System: WGS 1984 UTM Zone 18N Projection: Transverse Mercator Datum: WGS 1984 Units: Meter MODIS FIRE DETECTION: 1 OCT FEB 2016 The depiction and use of boundaries, geographic names and related data shown here are not warranted to be error-free nor do they imply official endorsement or acceptance by the United Nations. UNOSAT is a program of the United Nations Institute for Training and Research (UNITAR), providing satellite imagery and related geographic information, research and analysis to UN humanitarian and development agencies and their implementing partners. This work by UNITAR/UNOSAT is licensed under a Creative Commons Attribution-NonCommercialShareAlike 3.0 Unported License. Co nta c t Infor m a t ion: unos a t@ u nita r.or g 24 /7 H ot line : nita r.or g/un os at

Flag of Columbia - A Brief History

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