The remote sensing of ocean primary productivity: Use of a new data compilation to test satellite algorithms

1992 ◽  
Vol 97 (C2) ◽  
pp. 2279 ◽  
Author(s):  
William Balch ◽  
Robert Evans ◽  
Jim Brown ◽  
Gene Feldman ◽  
Charles McClain ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Primary Productivity ◽  
Data Compilation ◽  
Ocean Primary Productivity

scholarly journals Gross primary productivity of Brazilian Savanna (Cerrado) estimated by different remote sensing-based models

2021 ◽  
Vol 307 ◽  
pp. 108456
Author(s):  
Marcelo Sacardi Biudes ◽  
George Louis Vourlitis ◽  
Maísa Caldas Souza Velasque ◽  
Nadja Gomes Machado ◽  
Victor Hugo de Morais Danelichen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Brazilian Savanna

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

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.

Grassland afforestation impact on primary productivity: a remote sensing approach

2012 ◽  
Vol 16 (3) ◽  
pp. 390-403 ◽  
Author(s):  
M. Mercedes Vassallo ◽  
Hernán D. Dieguez ◽  
Martín F. Garbulsky ◽  
Esteban G. Jobbágy ◽  
José M. Paruelo
Keyword(s):  
Remote Sensing ◽  
Primary Productivity

scholarly journals Assessment of model estimates of land-atmosphere CO<sub>2</sub> exchange across Northern Eurasia

2015 ◽  
Vol 12 (14) ◽  
pp. 4385-4405 ◽  
Author(s):  
M. A. Rawlins ◽  
A. D. McGuire ◽  
J. S. Kimball ◽  
P. Dass ◽  
D. Lawrence ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Carbon ◽  
Residence Time ◽  
Primary Productivity ◽  
Ecosystem Respiration ◽  
Regional Scale ◽  
Northern Eurasia ◽  
Sink Strength ◽  
Vegetation Productivity ◽  
Co2 Sink

Abstract. A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m−2 yr−2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.

Remote sensing of biomass and annual net aerial primary productivity of a salt marsh

1984 ◽  
Vol 16 (2) ◽  
pp. 91-106 ◽  
Author(s):  
Michael A. Hardisky ◽  
Franklin C. Daiber ◽  
Charles T. Roman ◽  
Vytautas Klemas
Keyword(s):  
Remote Sensing ◽  
Salt Marsh ◽  
Primary Productivity
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