Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results.
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , , , , |
Idioma: | por |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/902317 |
Resumo: | At the Joint Research Centre (JRC) of the European Commission, a methodology has been developed to monitor the pan-tropical forest cover with remote sensing data for the years 1990-2000-2005 in Latin America, Southeast Asia and Africa on the basis of over 4000 sample units sample units with a dimension of 20 km by 20 km located at every full latitude and longitude degree confluence. From the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) instruments, images with low cloud impact from the epochs around the years 1990, 2000 and 2005 were selected and subsets covering the sample units were cut-out, pre-processed, segmented and classified in five different land cover classes in order to build global and regional statistics on tropical forest cover change. The data was validated in three steps, internal correction of wrongly classified objects, external (national or regional) expert validation and internal harmonization of the data. In this paper, the data collection and the workflow of the forest cover change assessment for the epochs 1990 and 2000 is presented. Parts of the results for the Brazilian Amazon have been validated by comparing with interpretations of corresponding samples carried out by the Instituto Nacional de Pesquisas Espaciais (INPE), showing a very high correlation. Further, the figure produced by INPE through the PRODES program on gross deforestation for the years 1990-2000 was compared to the figure calculated on basis of the JRC results for the respective area, where the JRC estimate that was ca. 10% higher than the INPE estimate. |
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Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results.Tropical forest coverObject-based classificationLandsatmonitoringAt the Joint Research Centre (JRC) of the European Commission, a methodology has been developed to monitor the pan-tropical forest cover with remote sensing data for the years 1990-2000-2005 in Latin America, Southeast Asia and Africa on the basis of over 4000 sample units sample units with a dimension of 20 km by 20 km located at every full latitude and longitude degree confluence. From the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) instruments, images with low cloud impact from the epochs around the years 1990, 2000 and 2005 were selected and subsets covering the sample units were cut-out, pre-processed, segmented and classified in five different land cover classes in order to build global and regional statistics on tropical forest cover change. The data was validated in three steps, internal correction of wrongly classified objects, external (national or regional) expert validation and internal harmonization of the data. In this paper, the data collection and the workflow of the forest cover change assessment for the epochs 1990 and 2000 is presented. Parts of the results for the Brazilian Amazon have been validated by comparing with interpretations of corresponding samples carried out by the Instituto Nacional de Pesquisas Espaciais (INPE), showing a very high correlation. Further, the figure produced by INPE through the PRODES program on gross deforestation for the years 1990-2000 was compared to the figure calculated on basis of the JRC results for the respective area, where the JRC estimate that was ca. 10% higher than the INPE estimate.RENÉ BEUCHLE, JOINT RESEARCH CENTRE OF THE EUROPEAN COMMISSION; HUGH DOUGLAS EVA, JOINT RESEARCH CENTRE OF THE EUROPEAN COMMISSION; EVARISTO EDUARDO DE MIRANDA, CNPM; WILSON ANDERSON HOLLER, CNPM; OSVALDO TADATOMO OSHIRO, CNPM; FRÉDERIC ACHARD, JOINT RESEARCH CENTRE OF THE EUROPEAN COMMISSION.BEUCHLE, R.EVA, H. D.MIRANDA, E. E. deHOLLER, W. A.OSHIRO, O. T.ACHARD, F.2011-10-04T11:11:11Z2011-10-04T11:11:11Z2011-10-04T11:11:11Z2011-10-0420112019-05-03T11:11:11ZArtigo em anais e proceedingsinfo:eu-repo/semantics/publishedVersionp. 2981-2988.In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011.http://www.alice.cnptia.embrapa.br/alice/handle/doc/902317porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-15T22:30:51Zoai:www.alice.cnptia.embrapa.br:doc/902317Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-15T22:30:51Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. |
title |
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. |
spellingShingle |
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. BEUCHLE, R. Tropical forest cover Object-based classification Landsat monitoring |
title_short |
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. |
title_full |
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. |
title_fullStr |
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. |
title_full_unstemmed |
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. |
title_sort |
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. |
author |
BEUCHLE, R. |
author_facet |
BEUCHLE, R. EVA, H. D. MIRANDA, E. E. de HOLLER, W. A. OSHIRO, O. T. ACHARD, F. |
author_role |
author |
author2 |
EVA, H. D. MIRANDA, E. E. de HOLLER, W. A. OSHIRO, O. T. ACHARD, F. |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
RENÉ BEUCHLE, JOINT RESEARCH CENTRE OF THE EUROPEAN COMMISSION; HUGH DOUGLAS EVA, JOINT RESEARCH CENTRE OF THE EUROPEAN COMMISSION; EVARISTO EDUARDO DE MIRANDA, CNPM; WILSON ANDERSON HOLLER, CNPM; OSVALDO TADATOMO OSHIRO, CNPM; FRÉDERIC ACHARD, JOINT RESEARCH CENTRE OF THE EUROPEAN COMMISSION. |
dc.contributor.author.fl_str_mv |
BEUCHLE, R. EVA, H. D. MIRANDA, E. E. de HOLLER, W. A. OSHIRO, O. T. ACHARD, F. |
dc.subject.por.fl_str_mv |
Tropical forest cover Object-based classification Landsat monitoring |
topic |
Tropical forest cover Object-based classification Landsat monitoring |
description |
At the Joint Research Centre (JRC) of the European Commission, a methodology has been developed to monitor the pan-tropical forest cover with remote sensing data for the years 1990-2000-2005 in Latin America, Southeast Asia and Africa on the basis of over 4000 sample units sample units with a dimension of 20 km by 20 km located at every full latitude and longitude degree confluence. From the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) instruments, images with low cloud impact from the epochs around the years 1990, 2000 and 2005 were selected and subsets covering the sample units were cut-out, pre-processed, segmented and classified in five different land cover classes in order to build global and regional statistics on tropical forest cover change. The data was validated in three steps, internal correction of wrongly classified objects, external (national or regional) expert validation and internal harmonization of the data. In this paper, the data collection and the workflow of the forest cover change assessment for the epochs 1990 and 2000 is presented. Parts of the results for the Brazilian Amazon have been validated by comparing with interpretations of corresponding samples carried out by the Instituto Nacional de Pesquisas Espaciais (INPE), showing a very high correlation. Further, the figure produced by INPE through the PRODES program on gross deforestation for the years 1990-2000 was compared to the figure calculated on basis of the JRC results for the respective area, where the JRC estimate that was ca. 10% higher than the INPE estimate. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-10-04T11:11:11Z 2011-10-04T11:11:11Z 2011-10-04T11:11:11Z 2011-10-04 2011 2019-05-03T11:11:11Z |
dc.type.driver.fl_str_mv |
Artigo em anais e proceedings |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011. http://www.alice.cnptia.embrapa.br/alice/handle/doc/902317 |
identifier_str_mv |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/902317 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
p. 2981-2988. |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
_version_ |
1817695201689337856 |