Exploring the Relationship between Remotely-Sensed Spectral Variables and Attributes of Tropical Forest Vegetation under the Influence of Local Forest Institutions

Agarwal, Shivani; Rocchini, Duccio; Marathe, Aniruddha; Nagendra, Harini

doi:10.3390/ijgi5070117

Cited by 5 publications

(3 citation statements)

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“…We advocate that others adapt our methods to monitor the BGI in additional TDFs and derive the BGI from land cover classification with a larger number of vegetation classes. Deriving the BGI from a more distinctive tree cover class could help overcome potential issues of interpretation similar to the Normalized Difference Vegetation Index (NDVI), a measure of live vegetation cover, where the NDVI value is not limited to photosynthetic activity from trees alone 21 . Finally, additional indicators of forest health in the CIHL can be developed that incorporate locally grounded values, knowledges, and needs 22 .…”

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confidence: 99%

Land cover and forest health indicator datasets for central India using very-high resolution satellite data

Khanwilkar,

Galletti,

Mondal

et al. 2023

Sci Data

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Satellite imagery has been used to provide global and regional estimates of forest cover. Despite increased availability and accessibility of satellite data, approaches for detecting forest degradation have been limited. We produce a very-high resolution 3-meter (m) land cover dataset and develop a normalized index, the Bare Ground Index (BGI), to detect and map exposed bare ground within forests at 90 m resolution in central India. Tree cover and bare ground was identified from Planet Labs Very High-Resolution satellite data using a Random Forest classifier, resulting in a thematic land cover map with 83.00% overall accuracy (95% confidence interval: 61.25%–90.29%). The BGI is a ratio of bare ground to tree cover and was derived by aggregating the land cover. Results from field data indicate that the BGI serves as a proxy for intensity of forest use although open areas occur naturally. The BGI is an indicator of forest health and a baseline to monitor future changes to a tropical dry forest landscape at an unprecedented spatial scale.

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Section: Usage Notesmentioning

confidence: 99%

Land cover and forest health indicator datasets for central India using very-high resolution satellite data

Khanwilkar,

Galletti,

Mondal

et al. 2023

Sci Data

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“…This special issue explores some of them, with challenging ideas facing different components of spatial patterns related to ecological processes, such as: (i) species variability over space [4][5][6][7][8][9][10][11]; and (ii) landscape dynamics [12,13].…”

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“…Beside the water-energy concept, remotely sensed spectral indices are used in this special issue to estimate different attributes of tropical forest vegetation under different anthropogenic impact [4].…”

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Space-Ruled Ecological Processes: Introduction to the Special Issue on Spatial Ecology

Rocchini

2018

IJGI

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This special issue explores most of the scientific issues related to spatial ecology and its integration with geographical information at different spatial and temporal scales. Papers are mainly related to challenging aspects of species variability over space and landscape dynamics, providing a benchmark for future exploration on this theme.The need for a spatial view in Ecology is a fact. Dealing with ecological changes over space and time represents a long-lasting theme, now faced by means of innovative techniques and modelling approaches (e.g., Chaudhary et al.This special issue explores some of them, with challenging ideas facing different components of spatial patterns related to ecological processes, such as: (i) species variability over space [4][5][6][7][8][9][10][11]; and (ii) landscape dynamics [12,13].Concerning biodiversity variability over space, key spatial datasets are needed to fully investigate biodiversity change in space and time, as shown by Geri et al. [7], who carried out innovative procedures to recover and properly map historical floristic and vegetation data for biodiversity monitoring. Furthermore, Dubois et al. [6] describe in detail one of the most important integrated observatory (Digital Observatory for Protected Areas, DOPA) to mobilize and use biodiversity data and spatial datasets, to asses the ecological status of protected areas.Once such data are gathered and integrated in a proper manner, Species Distribution Modelling is certainly one of the most powerful techniques used in ecology in which the geographical component makes the difference. In this special issue, Costa et al. [5] show that species misidentification might severely impact species distribution models once dealing with presence-only data.Besides identification problems, the model being used can lead to different results. Rodriguez de Rivera and Lopez-Quilez [10] propose a comparison among different species distribution models for forest inventories, promoting high flexibility models like additive models. In this view, one of the best models to study the spatial variability of species and communities is presented in this special issue by Leitao et al. [8], who demonstrate the power of Sparse Generalized Dissimilarity Modelling, by also providing a detailed description of the newly published R package sgdm.On the other side, species richness patterns are also considered, facing water-energy dynamics on terrestrial mammal and amphibian species over wide geographical regions [11]. Beside the water-energy concept, remotely sensed spectral indices are used in this special issue to estimate different attributes of tropical forest vegetation under different anthropogenic impact [4].Species distribution modelling-like techniques might also be applied to the spread of diseases threatening key species. For instance, Makori et al. [9] predict the spatial distribution of key honeybee pests in Kenya.In some cases, species-related data on distributions are not available. In such a case, relying on the variability of landscape-sc...

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Forest protection in Central India: do differences in monitoring by state and local institutions result in diverse social and ecological impacts?

et al. 2017

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Exploring the Relationship between Remotely-Sensed Spectral Variables and Attributes of Tropical Forest Vegetation under the Influence of Local Forest Institutions

Cited by 5 publications

References 49 publications

Land cover and forest health indicator datasets for central India using very-high resolution satellite data

Land cover and forest health indicator datasets for central India using very-high resolution satellite data

Space-Ruled Ecological Processes: Introduction to the Special Issue on Spatial Ecology

Forest protection in Central India: do differences in monitoring by state and local institutions result in diverse social and ecological impacts?

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