Estimativa de Albedo e Índice de Área Foliar na Amazônia (Albedo Estimate and Leaf Area Index in Amazonia)

Propôs-se, neste trabalho, estimar dados de albedo e Indice de Área Foliar (IAF) à superfície terrestre usando-se o sensor Thematic Mapper (TM) do satélite Landsat 5 e compará-lo com valores disponíveis na literatura científica. A região de estudo esta localizada no estado de Rondônia. Para a realização do estudo obtiveram-se quatro imagens orbitais do satélite Landsat 5 – TM, na órbita 231 e ponto 67, nas datas 13/07/2005, 13/05, 30/06 e 16/07 do ano de 2006, a que correspondem os dias Juliano 194, 133, 181 e 197, respectivamente. As correções geométricas para as imagens foram realizadas e geradas as cartas de albedo e IAF. O algoritmo SEBAL estimou satisfatoriamente os valores de albedo e IAF de superfícies sobre áreas de floresta (exceto para IAF) e pastagem.Palavras-chave: sensoriamento remoto, vegetacao, Floresta da Amazonia. Albedo Estimate and Leaf Area Index in Amazonia ABSTRACTThis study objectives the assessment of albedo and Leaf Area Index (LAI) data at surface using images from Thematic Mapper (TM) sensor onboard Landsat 5 satellite, and compare the results with values available in the scientific literature. The study area is located in the State of Rondônia. To carry out the study four orbital TM - Landsat images were obtained in the path 231 and row 67, for the dates of 07/13/2005, 06/30 and 07/16 of 2006 year, which correspond to the days 194, 181 and 197, respectively. The geometric correction for images was performed and maps of albedo and IAF were generated. The algorithm SEBAL estimated, satisfactorily, the values of albedo and IAF on the surface pasture and forest (except for LAI).Keywords: remote sensing, vegetation, Amazon Forest.

Download Full-text

INFLUÊNCIA DO DESMATAMENTO NO ÍNDICE DE ÁREA FOLIAR E TEMPERATURA DA SUPERFÍCIE NO CERRADO MATO-GROSSENSE

Nativa ◽

10.31413/nativa.v6i4.5367 ◽

2018 ◽

Vol 6 (4) ◽

pp. 364 ◽

Cited By ~ 1

Author(s):

Israel Oliveira Ivo ◽

Marcelo Sacardi Biudes ◽

Nadja Gomes Machado ◽

Vagner Marques Pavão

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Leaf Area Index ◽

Leaf Area ◽

Anthropogenic Activities ◽

Inverse Correlation ◽

Soil Surface ◽

Thematic Mapper ◽

Area Index ◽

Mato Grosso

A substituição do Cerrado mato-grossense para práticas agrícolas e a dinâmica fenológica alteram os índices biofísicos da superfície como a temperatura da superfície (Tsup) e o índice de área foliar (IAF). Assim, o objetivo desse estudo foi avaliar a variação do IAF e da Tsup por sensoriamento remoto em uma área de Cerrado no interior do estado de Mato Grosso. Imagens do sensor Thematic Mapper (TM) Landsat 5 foram utilizadas para estimar o IAF e a Tsup de uma área de Cerrado (CE), cana-de-açúcar (CA), pastagem (PA) e soja (SJ) em 2011. O IAF e a Tsup apresentaram correlação inversa. O IAF diminuiu e a Tsup aumentou ao longo da estação seca. Os maiores IAF e menores Tsup foram observados no CE, enquanto que os menores IAF e maiores Tsup foram observados na SJ. Os padrões temporais e espaciais do IAF e da Tsup na área de estudo ocorreram dirigidos pela precipitação, atividades antropogênicas e pelo próprio ciclo fenológico da vegetação.Palavras-chave: superfície do solo, antropização, aquecimento da superfície, sensoriamento remoto. INFLUENCE OF DEFORESTATION ON LEAF AREA INDEX AND SURFACE TEMPERATURE IN THE CERRADO OF MATO GROSSO ABSTRACT:The substitution of the Cerrado of Mato Grosso for agricultural practices and phenological dynamics alter the biophysical indexes of the surface such as surface temperature (Tsup) and leaf area index (LAI). Thus, the objective of this study was to evaluate the variation of LAI and Tsup by remote sensing in a Cerrado area in the state of Mato Grosso. The images of the Thematic Mapper (TM) Landsat 5 sensor were used to estimate the LAI and Tsup of an area of Cerrado (CE), sugarcane (CA), pasture (PA) and soybean (SJ) in 2011. The LAI and Tsup presented an inverse correlation. LAI declined and Tsup increased throughout the dry season. The higher LAI and lower Tsup were observed in the CE, while the lower LAI and higher Tsup were observed in SJ. The temporal and spatial patterns of LAI and Tsup in the study area were driven by precipitation, anthropogenic activities and by the phenological cycle of vegetation itself.Keywords: soil surface, anthropization, surface heating, remote sensing.

Download Full-text

Retrieval and Comparison of Forest Leaf Area Index Based on Remote Sensing Data from AVNIR-2, Landsat-5 TM, MODIS, and PALSAR Sensors

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi6060179 ◽

2017 ◽

Vol 6 (6) ◽

pp. 179 ◽

Cited By ~ 3

Author(s):

Wei Chen ◽

Hang Yin ◽

Kazuyuki Moriya ◽

Tetsuro Sakai ◽

Chunxiang Cao

Keyword(s):

Remote Sensing ◽

Leaf Area Index ◽

Leaf Area ◽

Remote Sensing Data ◽

Area Index ◽

Sensing Data ◽

Landsat 5 Tm

Download Full-text

Estimation of Forest Leaf Area Index from Remote Sensing Data Using the Algorithm Based on Geometric-optical Model

Geo-information Science ◽

10.3724/sp.j.1047.2012.00358 ◽

2012 ◽

Vol 14 (3) ◽

pp. 358-365

Author(s):

Hanyue CHEN ◽

Wenjiang HUANG ◽

Zheng NIU ◽

Shuai GAO

Keyword(s):

Remote Sensing ◽

Leaf Area Index ◽

Leaf Area ◽

Optical Model ◽

Remote Sensing Data ◽

Area Index ◽

Sensing Data

Download Full-text

Remote Sensing to Study Mangrove Fragmentation and Its Impacts on Leaf Area Index and Gross Primary Productivity in the South of Peninsular Malaysia

Remote Sensing ◽

10.3390/rs13081427 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1427

Author(s):

Kasturi Devi Kanniah ◽

Chuen Siang Kang ◽

Sahadev Sharma ◽

A. Aldrie Amir

Keyword(s):

Remote Sensing ◽

Leaf Area Index ◽

Leaf Area ◽

Primary Productivity ◽

Peninsular Malaysia ◽

Area Index ◽

Mangrove Area ◽

The Mean ◽

Shape Complexity ◽

The Impact

Mangrove is classified as an important ecosystem along the shorelines of tropical and subtropical landmasses, which are being degraded at an alarming rate despite numerous international treaties having been agreed. Iskandar Malaysia (IM) is a fast-growing economic region in southern Peninsular Malaysia, where three Ramsar Sites are located. Since the beginning of the 21st century (2000–2019), a total loss of 2907.29 ha of mangrove area has been estimated based on medium-high resolution remote sensing data. This corresponds to an annual loss rate of 1.12%, which is higher than the world mangrove depletion rate. The causes of mangrove loss were identified as land conversion to urban, plantations, and aquaculture activities, where large mangrove areas were shattered into many smaller patches. Fragmentation analysis over the mangrove area shows a reduction in the mean patch size (from 105 ha to 27 ha) and an increase in the number of mangrove patches (130 to 402), edge, and shape complexity, where smaller and isolated mangrove patches were found to be related to the rapid development of IM region. The Moderate Resolution Imaging Spectro-radiometer (MODIS) Leaf Area Index (LAI) and Gross Primary Productivity (GPP) products were used to inspect the impact of fragmentation on the mangrove ecosystem process. The mean LAI and GPP of mangrove areas that had not undergone any land cover changes over the years showed an increase from 3.03 to 3.55 (LAI) and 5.81 g C m−2 to 6.73 g C m−2 (GPP), highlighting the ability of the mangrove forest to assimilate CO2 when it is not disturbed. Similarly, GPP also increased over the gained areas (from 1.88 g C m−2 to 2.78 g C m−2). Meanwhile, areas that lost mangroves, but replaced them with oil palm, had decreased mean LAI from 2.99 to 2.62. In fragmented mangrove patches an increase in GPP was recorded, and this could be due to the smaller patches (<9 ha) and their edge effects where abundance of solar radiation along the edges of the patches may increase productivity. The impact on GPP due to fragmentation is found to rely on the type of land transformation and patch characteristics (size, edge, and shape complexity). The preservation of mangrove forests in a rapidly developing region such as IM is vital to ensure ecosystem, ecology, environment, and biodiversity conservation, in addition to providing economical revenue and supporting human activities.

Download Full-text