Forest biomass estimation using remote sensing and field inventory: a case study of Tripura, India

Pandey, Prem C.; Srivastava, Prashant K.; Chetri, Tilok; Choudhary, Bal Krishan; Kumar, Pavan

doi:10.1007/s10661-019-7730-7

Cited by 23 publications

(6 citation statements)

References 49 publications

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“…The conducted research has proved a high NDVI and LAI correlation and its dependence on field and laboratory data, revealed by other authors as well [27][28][29]. In particular, work [27] presents the results of studies carried out in winter time in the north of Europe, but works [28] and [19] in the tropical forest in northern India and in the Tripura region (India).…”

Section: Discussionmentioning

confidence: 61%

Optical Parameters of the Tilia Cordata Mill. Assimilation Apparatus

Sultanova¹,

Мартынова²,

Odintsov³

et al. 2022

(MMEP

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Morphometric indicators of trees' assimilative apparatus, including their reflection and light-absorbing properties, largely determine their physiological processes. Leaf initiation and development depend on chlorophyll resulting from photosynthesis, water absorption, its movement through a tree and evaporation. The aim of the paper is to evaluate leaf optical properties of Tilia cordata Mill. It was found that optical coefficients of leaf blades vary depending on the time of sample collection: at the end of the growing season, the leaf blade absorptance (Ab) ranges from 68.9% to 72.4%. During the intensive formation of Tilia flowers, the Ab coefficient decreases to 59.2%. It starts to rise before the beginning of the Tilia fruit maturation. The transmittance, Tr, is also lower at the period of intense flower development. Estimating NDVI (vegetation index) and LAI (leaf area index) from Sentinel-2 satellite imagery showed that the ratio between these indices (NDVI-LAI) changes during the entire growing season. The NDVI-LAI correlation varied up to the strongest one during the entire phenological cycle.

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Section: Discussionmentioning

confidence: 61%

Optical Parameters of the Tilia Cordata Mill. Assimilation Apparatus

Sultanova¹,

Мартынова²,

Odintsov³

et al. 2022

(MMEP

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“…The error matrix was created based on the sample site selected randomly for assessing the accuracy of the LULC classes it was indicated that the overall accuracy was 97.09% and the Kappa coefficient was 0.95 (Table 2). Forests have the potential to absorb CO 2 from the atmosphere, which is stored as woody biomass (Pandey et al, 2019). The study carried out by The NDVI map generated shows that the value ranging from -0.23 to 0.74, indicating waterbody to very dense forest respectively.…”

Section: Methodsmentioning

confidence: 99%

The Assessment of land use land cover and carbon sequestration in forests of Joida Taluk of Uttar Kannada district using Remote sensing technique

Koppad

Banavasi²,

Sarfin

2020

JANS

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The study was conducted in Joida Taluk of Uttar Kannada district, Karnataka to assess the land use land cover (LULC) and carbon sequestration of the forest during the year 2019-20. The ground truth data for different LULC was collected using GPS, and data was used for classification of IRS LISS 4 data using maximum likelihood classifier in ERDAS imagine software. The sample plots of 23.2 m X 23.2 m were laid out randomly in forests and growth parameters (tree height and diameter) were recorded, and biomass was estimated using the standard formula. There are eight LULC classes’ viz., dense forest, moderately dense forest, open/sparse forest, scrub forest, agriculture, settlement, horticulture plantation and waterbody. The overall accuracy of the classification was 97.09%. The total biomass in Joida Taluk from four forest classes (dense forest, moderately dense forest, open/sparse forest and scrub forest) was 44.16 million m3 and carbon sequestered was 15.57 million tonnes. The NDVI values ranging from -0.23 to 0.74, indicating a higher value for dense forest. Based on this study, it is concluded that forests have potential in carbon sequestration, which in turn helps in mitigating the climate change.

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“…South America placed second in the number of studies conducted [40,47,48], with African tropical and subtropical forest regions lagging behind. We noted that the area and extent of the study sites ranged between 4 ha [39] and 6292.68 ha [49]. The majority of the studies identified by the selection criteria utilized optical sensor imagery to predict AGB and AGC.…”

Section: Aboveground Biomass and Carbon Estimation Using Remote Sensingmentioning

confidence: 99%

Two Decades Progress on the Application of Remote Sensing for Monitoring Tropical and Sub-Tropical Natural Forests: A Review

Gyamfi-Ampadu

Gebreslasie

2021

Forests

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Forest covers about a third of terrestrial land surface, with tropical and subtropical zones being a major part. Remote sensing applications constitute a significant approach to monitoring forests. Thus, this paper reviews the progress made by remote sensing data applications to tropical and sub-tropical natural forest monitoring over the last two decades (2000–2020). The review focuses on the thematic areas of aboveground biomass and carbon estimations, tree species identification, tree species diversity, and forest cover and change mapping. A systematic search of articles was performed on Web of Science, Science Direct, and Google Scholar by applying a Boolean operator and using keywords related to the thematic areas. We identified 50 peer-reviewed articles that studied tropical and subtropical natural forests using remote sensing data. Asian and South American natural forests are the most highly researched natural forests, while African natural forests are the least studied. Medium spatial resolution imagery was extensively utilized for forest cover and change mapping as well as aboveground biomass and carbon estimation. In the latest studies, high spatial resolution imagery and machine learning algorithms, such as Random Forest and Support Vector Machine, were jointly utilized for tree species identification. In this review, we noted the promising potential of the emerging high spatial resolution satellite imagery for the monitoring of natural forests. We recommend more research to identify approaches to overcome the challenges of remote sensing applications to these thematic areas so that further and sustainable progress can be made to effectively monitor and manage sustainable forest benefits.

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Forest biomass estimation using remote sensing and field inventory: a case study of Tripura, India

Cited by 23 publications

References 49 publications

Optical Parameters of the Tilia Cordata Mill. Assimilation Apparatus

Optical Parameters of the Tilia Cordata Mill. Assimilation Apparatus

The Assessment of land use land cover and carbon sequestration in forests of Joida Taluk of Uttar Kannada district using Remote sensing technique

Two Decades Progress on the Application of Remote Sensing for Monitoring Tropical and Sub-Tropical Natural Forests: A Review

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