Characterizing land cover dynamics using multi-temporal imagery

Alves, Diógenes Salas; Skole, David L.

doi:10.1080/01431169608949049

Cited by 83 publications

(52 citation statements)

References 4 publications

(1 reference statement)

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“…This means that seconda U growth is recleared quickly, typically after 4--5 years. This result is consistent with the study of Alves and Skole (1996).…”

Section: Discussionsupporting

confidence: 83%

“…The deforestation rate is 1.7% for 1994. This value is higher but consistent with the 1.5 percent estimate calculated by Alves and Skole (1996) in 1992 over a larger area.…”

Section: Discussionsupporting

confidence: 79%

“…4c). A portion of these clearings may have been abandoned in 1992, given the high rates of land abandonment in the area (Alves and Skole, 1996), so our accuracy estimates may underestimate the performance of the Landsat TM classifieation.…”

Section: Sir-c and Landsat Tm Land-cover Mappingmentioning

confidence: 97%

“…Much of the land is now in pasture of various quality for cattle and in secondary growth of various ages, Smaller plots are planted with coffee, maize, beans, and other crops. Unproductive fields are quickly' abandoned, typically after 3-4 years, returning to forest regrowth (Alves and Skole, 1996). Regrowth is typically vigorous and dominated by several pioneer species, The data set utilized in this study is described in Table 1.…”

Section: Study Sitementioning

confidence: 99%

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Mapping deforestation and secondary growth in Rondonia, Brazil, using imaging radar and thematic mapper data

Rignot¹,

Salas²,

Skole³

1997

Remote Sensing of Environment

133

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“…This means that seconda U growth is recleared quickly, typically after 4--5 years. This result is consistent with the study of Alves and Skole (1996).…”

Section: Discussionsupporting

confidence: 83%

“…The deforestation rate is 1.7% for 1994. This value is higher but consistent with the 1.5 percent estimate calculated by Alves and Skole (1996) in 1992 over a larger area.…”

Section: Discussionsupporting

confidence: 79%

Section: Sir-c and Landsat Tm Land-cover Mappingmentioning

confidence: 97%

Section: Study Sitementioning

confidence: 99%

See 2 more Smart Citations

Mapping deforestation and secondary growth in Rondonia, Brazil, using imaging radar and thematic mapper data

Rignot¹,

Salas²,

Skole³

1997

Remote Sensing of Environment

133

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“…Diversos autores mapearam em escala local a ocorrência de vegetação secundária e encontraram relações desta com os ambientes físico e sócio-econômico da região (Alves & Skole 1996;Nelson et al, 2000;Steininger, 2000;Roberts et al, 2002;Alves et al, 2003;Lu et al, 2003a;Espírito-Santo et al, 2005;). Estimativas do total de área de vegetação secundária na AML foram realizadas através de métodos amostrais, considerando quase sempre um pequeno número de amostras, ou por medidas com base em dados de sensoriamento remoto de baixa resolução.…”

Section: Introductionunclassified

Estimativa de área de vegetação secundária na Amazônia Legal Brasileira

et al. 2010

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A vegetação secundária tem funções relevantes para os ecossistemas, tais como a fixação de carbono atmosférico, a manutenção da biodiversidade, o estabelecimento da conectividade entre remanescentes florestais, manutenção dos regime hidrológico e a recuperação da fertilidade do solo. O objetivo deste trabalho é, através de uma abordagem amostral, estimar a área ocupada por vegetação secundária na Amazônia Legal Brasileira (AML) em 2006. A amostragem se baseia em uma abordagem estratificada pelo grau de desflorestamento das cenas LANDSAT-TM que recobrem a AML. Foram selecionadas 26 cenas para o ano de 2006, distribuídas em sete estratos conforme o percentual de desflorestamento, nas quais foram mapeadas as áreas de vegetação secundária a partir de técnicas de classificação de imagens. Foi desenvolvido um modelo multivariado de regressão para estimar a área de vegetação secundária utilizando como variáveis independentes a área de desflorestamento, a área de hidrografia, a estrutura agrária, e área das unidades de conservação. A análise de regressão encontrou um R 2 ajustado de 0,84 , e coeficientes positivos para a proporção de hidrografia na imagem (2,055) e para a estrutura agrária (0,197), e coeficientes negativos para o grau de desflorestamento na imagem (-0,232) e para a proporção de Unidades de Conservação na imagem (-0,262 Estimation of secondary vegetation area in the Brazilian Legal Amazon ABSTRACTSecondary vegetation has many relevant functions to the ecosystems such as atmospheric carbon fixation , maintenance of biodiversity, establishment of connectivity among forest remnants, maintenance of hydrological regime, and restoration of soil fertility. The objective of this work is to estimate the area occupied by secondary vegetation in the Brazilian Legal Amazon (BLA) for 2006 using a sampling scheme. The sampling is based on a stratified approach according to the degree of deforestation observed in the 229 TM-Landsat scenes that cover the BLA. Thus, 26 scenes were selected for 2006 and distributed into seven strata, according to their degree of deforestation, in which secondary vegetation areas were mapped. A regression model was constructed to estimate secondary vegetation area in the remaining images using deforestation area, hydrographic area, agrarian structure , and area of conservation units, as independent variables. The regression analysis found an adjusted R 2 of 0.84 and positive coefficients for the proportion of hydrography in the image (2.055) and for the agrarian structure (0.197), while negative coefficients for the degree of deforestation in the image (-0.232) as well as for the proportion of Conservation Unity (-0.262

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Tropical Forest Resource Assessment by Remote Sensing

Boyd

2000

Encyclopedia of Analytical Chemistry

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The earth's tropical forests are a global resource, requiring action for their wise utilization, management and protection at spatial scales from the local through to the global. The acquisition of data pertaining to tropical forest resources presents many challenges, 1 many of which may be overcome through the use of remote sensing. Reasons for the adoption of remote sensing for the assessment of tropical forest resources are compelling. Remote sensing can be used to observe the dynamics of tropical forests at almost any level of detail. It allows the frequent measurement and monitoring of the earth's tropical forests on a continuous basis, from which accurate and informed judgments on their resources at any given time can be made. Accordingly, there has been progressive evolution of remote sensing approaches for the collection of tropical forest resource information. With the imminent launch of new spaceborne sensors which will be able to acquire more information on tropical forests, remote sensing will continue to be a crucial tool in the assessment of tropical forest resources.

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Characterizing land cover dynamics using multi-temporal imagery

Cited by 83 publications

References 4 publications

Mapping deforestation and secondary growth in Rondonia, Brazil, using imaging radar and thematic mapper data

Mapping deforestation and secondary growth in Rondonia, Brazil, using imaging radar and thematic mapper data

Estimativa de área de vegetação secundária na Amazônia Legal Brasileira

Tropical Forest Resource Assessment by Remote Sensing

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