Summary. Deforestation report for the Brazilian Amazon (February 2015) SAD



Similar documents
INPE s Brazilian Amazon Deforestation and Forest Degradation Program. Dalton M. Valeriano (dalton@dsr.inpe.br) Program Manager

Analyzing temporal and spatial dynamics of deforestation in the Amazon: a case study in the Calha Norte region, State of Pará, Brazil

How To Map Forest Change With A Gca

Brazil s Response to Lower Commodity Prices Will Infrastructure Improvements Support Further Expansion?

Industrial area with Hangar. Land area: sqm Hangar area: sqm Office area: 250 sqm Brazil Espírito Santo Serra Highway BR 101 North

Remote Sensing of Environment

TerraAmazon - The Amazon Deforestation Monitoring System - Karine Reis Ferreira

National Institute for Space Research (INPE) Earth Science System Center (CCST)

REDD+ SOCIAL AND ENVIRONMENTAL PRINCIPLES AND CRITERIA

VCS REDD Methodology Module. Methods for monitoring forest cover changes in REDD project activities

Estimating Central Amazon forest structure damage from fire using sub-pixel analysis

Report of the technical assessment of the proposed forest reference emission level of Brazil submitted in 2014

CRITICAL Protected Areas in the Amazon in the period of 2012 to 2014

Brazil February Production Update and Weekly Crop Condition Report

THE EVOLUTION OF THE POPULATION- BASED CANCER REGISTRIES IN BRAZIL: A PERFORMANCE EVALUATION

TerraColor White Paper

Changes in forest cover applying object-oriented classification and GIS in Amapa- French Guyana border, Amapa State Forest, Module 4

Three Essential Strategies. For Reducing Deforestation. December 2007

INPE Spatial Data Infrastructure for Big Spatiotemporal Data Sets. Karine Reis Ferreira (INPE-Brazil)

NEW BRAZILIAN ENVIRONMENTAL CRIMES LAW: AN ANALYSIS OF ITS EFFECTIVENESS TO PROTECT THE FORESTS OF AMAZONIA 1

MODIS IMAGES RESTORATION FOR VNIR BANDS ON FIRE SMOKE AFFECTED AREA

Remote Sensing Method in Implementing REDD+

Obtaining and Processing MODIS Data

Application of Invest`s Sedimentation Retention model for restoration benefits forecast at Cantareira Water Supply System

REDD in Brazil: A focus on the Amazon

STAR Algorithm and Data Products (ADP) Beta Review. Suomi NPP Surface Reflectance IP ARP Product

Using Remote Sensing to Monitor Soil Carbon Sequestration

Deforestation in the Amazon

Moderate- and high-resolution Earth Observation data based forest and agriculture monitoring in Russia using VEGA Web-Service

Remote Sensing an Introduction

CONTENTS AREA STUDIES - REGIONAL SUSTAINABLE DEVELOPMENT: BRAZIL

Who is responsible for the destruction of the Amazon rainforest?

Monitoring alterations in vegetation cover and land use in the Upper Paraguay River Basin Brazilian Portion Period of Analysis: 2002 to 2008

A KNOWLEDGE-BASED APPROACH FOR REDUCING CLOUD AND SHADOW ABSTRACT

Population Ecology. Life History Traits as Evolutionary Adaptations

National and Sub-national Carbon monitoring tools developed at the WHRC

Forest Carbon Monitoring: A Review of Selected Remote Sensing and Carbon Measurement Tools for REDD+

Measurement of the effect of biomass burning aerosol on inhibition of cloud formation over the Amazon

TerraLib as an Open Source Platform for Public Health Applications. Karine Reis Ferreira

Deforestation Slowdown in the Legal Amazon: Prices or Policies?

LANDSAT 8 Level 1 Product Performance

The Need for International Weather Data and Related Products at the U.S. Department of Agriculture. Presented to. CoCoRaHS

2.3 Spatial Resolution, Pixel Size, and Scale

RESULT, ANALYSIS AND DISCUSSION

HIGH SPATIAL RESOLUTION IMAGES - A NEW WAY TO BRAZILIAN'S CARTOGRAPHIC MAPPING

Land Cover Mapping of the Comoros Islands: Methods and Results. February ECDD, BCSF & Durrell Lead author: Katie Green

Use of remote sensing for crop yield and area estimates in Southern Brazil

Using Remote Sensing Imagery to Evaluate Post-Wildfire Damage in Southern California

Cloud Masking and Cloud Products

Review for Introduction to Remote Sensing: Science Concepts and Technology

Hyperspectral Satellite Imaging Planning a Mission

Manaus Free Trade Zone. Meeting with Taipei Delegation Brasília, October 25 th, 2013

FOOD SECURITY, LABOR MARKET AND POVERTY OF THE BIO- ECONOMY IN BRAZIL

UTM: Universal Transverse Mercator Coordinate System

A Hybrid Architecture for Mobile Geographical Data Acquisition and Validation Systems

The USGS Landsat Big Data Challenge

Data Processing Flow Chart

GLOBAL FORUM London, October 24 & 25, 2012

Forestry Thematic Exploitation Platform Earth Observation Open Science 2.0

Transcription:

Summary In February 2015, more than half (59%) of the forest area of the Brazilian Amazon was covered by clouds, a coverage lower than in February 2014 (69%). The States with the highest cloud cover were Amapá (95%), Acre (77%) and Pará (72%). During the period analyzed, and under those cloud conditions, 42 square kilometers of deforestation were detected by SAD in the Brazilian Amazon. That represents a 282% increase in relation to February 2014 when deforestation totaled 11 square kilometers. Antônio Fonseca, Carlos Souza Jr. & Adalberto Veríssimo (Imazon) In February 2015, deforestation was largely concentrated in Mato Grosso (37%) and Roraima (28%), with a lower occurrence in Amazonas (16%), Pará (14%) and Rondônia (5%). Deforestation accumulated during the period from August 2014 to February 2015, corresponding to the first seven months of the official calendar for measuring deforestation, reached 1,702 square kilometers. There was a 215% increase in deforestation in relation to the previous period (August 2013 to February 2014) when it reached 540 square kilometers. Degraded forests in the Brazilian Amazon totaled 49 square kilometers in February 2015. In relation to February 2014, when forest degradation totaled 50 square kilometers there was a 2% reduction. Forest Transparency for the Brazilian Amazon 1

Deforestation statistics According to SAD, deforestation (total suppression of the forest for other alternative land uses) reached 42 square kilometers in February 2015 (Figure 1 and Figure 2). Figure 1. Deforestation from August 2013 to February 2015 in the Brazilian Amazon Figure 2. Deforestation and forest degradation in February 2015 in the Brazilian Amazon (Source: Imazon/ SAD). Forest Transparency for the Brazilian Amazon 2

In February 2015, deforestation was concentrated in Mato Grosso (37%) and Roraima (28%), with a lower occurrence in Amazonas (16%), Pará (14%) and Rondônia (5%) (Figure 3). The deforestation accumulated during the period from August 2014 to February 2015, corresponding to the first seven months of the official calendar for measuring deforestation, reached 1,702 square kilometers. There was an increase of 215% in deforestation in relation to the previous period (August 2013 to February 2014) when it reached 540 square kilometers. Considering the first seven months of the current deforestation calendar (August 2014 to February 2015), Mato Grosso leads the ranking with 35% of the total deforested during the period. Next come Pará (25%) and Rondônia (20%). In relative terms, there was a significant increase of 681% in Mato Grosso and 238% in Pará. In absolute terms, Mato Grosso leads the ranking of accumulated deforestation with 595 square kilometers, followed by Pará (433 square kilometers) and Rondônia, with 342 square kilometers (Table 1). Table 1. Evolution of deforestation among States in the Brazilian Amazon from August 2013 to February 2014 and August 2014 to February 2015 * Data from Maranhão were not analyzed. Figure 3. Percentage of deforestation in States of the Brazilian Amazon in February 2015 Forest Transparency for the Brazilian Amazon 3

Forest degradation In February 2015, SAD recorded 49 square kilometers of degraded forests (forests intensely exploited by logging activity and/or burned) (Figures 2 and 4). Of that total, the great majority (99%) occurred in Mato Grosso, followed by Rondônia (1%). Table 2. Evolution of forest degradation among States in the Brazilian Amazon from August 2013 to February 2014 and August 2014 to February 2015 * Data from Maranhão were not analyzed. Figure 4. Forest Degradation from August 2013 to February 2015 in the Brazilian Amazon Forest Transparency for the Brazilian Amazon 4

Geography of deforestation In February 2015, the majority (79%) of deforestation occurred in areas that were private or under various stages of possession. The remaining deforestation was recorded in Land Reform Settlements (18%), Conservation Units (2%) and Indigenous Lands (1%) (Table 3). Land Reform Settlements SAD recorded 32.5 square kilometers of deforestation in Land Reform Settlements in February 2015 (Figure 5). The Settlements most affected by deforestation were PA Acari (Rorainópolis; Roraima), PA Ajarani (Iracema; Roraima) and PDS Tepequém (Amajari; Roraima). Table 3. Deforestation by land title category in February 2015 in the Brazilian Amazon (Source: Imazon/ SAD). Figure 5. Land Reform Settlements deforested in February 2015 in the Brazilian Amazon Forest Transparency for the Brazilian Amazon 5

Protected Areas In the month of February 2015, SAD detected only 0.9 square kilometer of deforestation in the Florex Rio Preto-Jacundá State Conservation Unit (Rondônia). In the case of Indigenous Lands, in February 2015 only 0.5 square kilometer of deforestation was detected in TI Arary (Amazonas). Critical municipalities In February 2015, the most deforested municipalities were: Porto dos Gaúchos (Mato Grosso) and Vitória do Xingu (Pará) (Figure 6 and 7). Figure 7. Municipalities with the largest areas deforested in February 2015 Figure 6. Most deforested municipalities in the Brazilian Amazon in February 2015 (Source: Imazon /SAD). Forest Transparency for the Brazilian Amazon 6

Cloud and shadow cover In February 2015, it was possible with SAD 41% to monitor of the forest area in the Brazilian Amazon. The other 59% of forest territory was covered by clouds, which made it difficult to detect deforestation and forest degradation. The States with the highest cloud cover were Amapá (95%) and Acre (77%). Because of that, the data for deforestation and forest degradation in February 2015 may be underestimated (Figure 8). SAD-EE Figure 8. Area with cloud and shadow in February 2015 in the Brazilian Amazon. * The portion of Maranhão that is part of the Brazilian Amazon was not analyzed. Since July 2012 deforestation and forest degradation detection alerts have been performed using the Google Earth Engine platform (EE), with the new SAD EE version. That system was developed in collaboration with Google and uses the same process already employed by SAD 3.0 (Box I), with reflectance images from MODIS to generate the deforestation and forest degradation alerts. Forest Transparency for the Brazilian Amazon 7

BOX I: SAD 3.0 Since August 2009, SAD has had some new features. First, we created a graphic interface to integrate all of the image processing programs used in SAD. Next, we began to compute deforestation in areas that were covered by clouds in the previous months in a new class. Finally, deforestation and degradation are detected with pairs of NDFI images using a change detection algorithm. The principal method continues to be the same as with SAD 2.0 as described below. SAD generates a temporal mosaic of daily MODIS images from the MOD09GQ and MOD09GA products for filtering clouds. Next, we use a technique for fusing different spectral resolution bands, i.e. with pixels of different sizes. In this case, we made a change in scale from 5 bands with 500 meter pixels in MODIS to 250 meters. That allowed us to improve the spectral mixture model and provided the capacity for estimating the abundance of Vegetation, Soils and Non-Photosynthetic Vegetation (NPV) components (Vegetation, Soil and Shadow) to calculate the NDFI, with the following equation: NDFI = (VGs (NPV + Soil) (VGs +NPV+Soil) Where VGs is the Vegetation component normalized for shadow given by: Vgs = Vegetation/ (1- Shadow) The NDFI varies from -1 (pixel with 100% of exposed soil) to 1 (pixel with > 90% of forest vegetation). Thus, we have a continuous image that shows the transition from deforested areas, going through degraded forests, until reaching forest without signs of disturbances. Detection of deforestation and degradation this month involved a difference in the NDFI images from consecutive months. Thus, a reduction in the NDFI values of from -200 to -50 indicates possible deforested areas and from -49 to -20 indicates signs of degradation. SAD 3.0 Beta is compatible with previous versions with a (SAD 1.0 and 2.0), because the threshold for detecting deforestation was calibrated to generate the same type of response obtained by the previous method. SAD has been in operation in the State of Mato Grosso since August 2006 and in the Legal Amazon since August 2008. In this bulletin, we present the monthly data generated by SAD from August 2013 to February 2015. Forest Transparency for the Brazilian Amazon 8

Team reasponsible Support General Coordination: Carlos Souza Jr. e Adalberto Veríssimo (Imazon). Technical Coordination: Antônio Fonseca. Team: João Siqueira e Marcelo Justino (Image interpretation), Kátia Pereira and Victor Lins (ImazonGeo) e Bruno Oliveira (Communication). Data source Statistics for deforestation are generated using data from SAD (Imazon); Data from INPE- Deforestation (PRODES) http://www.obt.inpe.br/prodes/ Acknowledgements Google Earth Engine Team http://earthengine.google.org/ Partnerships State Secretariat for the Environment and Sustainability of Pará (SEMA) State Secretariat for the Environment of Mato Grosso (SEMA) Federal Public Prosecution Service in Pará State Public Prosecution Service of Pará State Public Prosecution Service of Roraima State Public Prosecution Service of Amapá State Public Prosecution Service of Mato Grosso Instituto Centro de Vida (ICV- Mato Grosso) Forest Transparency for the Brazilian Amazon 9