Evaluation of vegetation indices for rangeland biomass estimation in the Kimberley area of Western Australia

The objective of this paper is to test the relationships between Above Ground Biomass (AGB) and remotely sensed vegetation indices for AGB assessments in the Kimberley area in Western Australia. For 19 different sites, vegetation indices were derived from eight Landsat ETM+ scenes over a period of two years (2011–2013). The sites were divided into three groups (Open plains, Bunch grasses and Spinifex) based on similarities in dominant vegetation types. Dry and green biomass fractions were measured at these sites. Single and multiple regression relationships between vegetation indices and green and total AGB were calibrated and validated using a "leave site out" cross validation. Four tests were compared: (1) relationships between AGB and vegetation indices combining all sites; (2) separate relationships per site group; (3) multiple regressions including selected vegetation indices per site group; and (4) as in 3 but including rainfall and elevation data. Results indicate that relationships based on single vegetation indices are moderately accurate for green biomass in wide open plains covered with annual grasses. The cross-validation results for green AGB improved for a combination of indices for the Open plains and Bunch grasses sites, but not for Spinifex sites. When rainfall and elevation data are included, cross validation improved slightly with a Q2 of 0.49–0.72 for Open plains and Bunch grasses sites respectively. Cross validation results for total AGB were moderately accurate (Q2 of 0.41) for Open plains but weak or absent for other site groups despite good calibration results, indicating strong influence of site-specific factors

Remotely sensed and modelled pasture biomass, land condition and the potential to improve grazing-management decision tools across the Australian rangelands

This report assesses the potential for expanding on current capacity to monitor land condition using remotely sensed fractional cover products to improve biomass estimation, animal productivity, pasture growth models and grazing decision tools (e.g. safe carrying capacity) across the Australian rangelands. We focus on northern Australia and include relevant research and implementation from southern Australia where appropriate

Lidar Remote Sensing Of Forest Canopy Structure: An Assessment Of The Accuracy Of Lidar And Its Relationship To Higher Trophic Levels

Light detection and ranging (LiDAR) data can provide detailed information about three-dimensional forest horizontal and vertical structure that is important to forest productivity and wildlife habitat. Indeed, LiDAR data have been shown to provide accurate estimates to forest structural parameters and measures of higher trophic levels (e.g., avian abundance and diversity). However, links between forest structure and tree function have not been evaluated using LiDAR. This study was designed and scaled to assess the relationship of LiDAR to multiple aspects of forest structure and higher trophic levels (arthropod and bird populations), which included the ground-based collection of percent crown and understory closure, as well as arthropod and avian abundance and diversity data. Additional plot-based measures were added to assess the relationship of LiDAR to forest health and productivity. High-resolution discrete-return LiDAR data (flown summer of 2009) were acquired for the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA. LiDAR data were classified into four canopy structural categories: 1) high crown and high understory closure, 2) high crown and low understory closure, 3) low crown and high understory closure, and 4) low crown and low understory closure. Nearby plots from each of the four LiDAR categories were grouped into blocks to assess the spatial consistency of data. Ground-based measures of forest canopy structure, site, stand and individual tree measures were collected on nine 50 m-plots from each LiDAR category (36 plots total), during summer of 2012. Analysis of variance was used to assess the relationships between LiDAR and a suite of tree function measures. Our results show the novel ability of LiDAR to assess forest health and productivity at the stand and individual tree level. We found significant correspondence between LiDAR categories and our ground-based measures of tree function, including xylem increment growth, foliar nutrition, crown health, and stand mortality. Furthermore, we found consistent reductions in xylem increment growth, decreases in foliar nutrition and crown health, and increases in stand mortality related to high understory closure. This suggests that LiDAR measures can reflect competitive interactions, not just among overstory trees for light, but also interactions between overstory trees and understory vegetation for resources other than light (e.g., nutrients). High-resolution LiDAR data show promise in the assessment of forest health and productivity related to tree function

Estimating Above Ground Biomass using Remote Sensing in the Sub-Tropical Climate Zones of Australia

The study focused on assessing the total above ground biomass using remote sensing in the Kimberley rangelands of Western Australia. Remote sensing has the advantage that it can rapidly provide estimates non-destructively on a large scale with a high temporal frequency. In this thesis a field sampling protocol was developed and mono- and multi-temporal above ground biomass estimation models could be calibrated and validated with field based measurements for the most significant vegetation types

Review of Remote Sensing Techniques for the Visualization of Mangroves, Reefs, Fishing Grounds, and Molluscan Settling Areas in Tropical Waters

Globally there has been tremendous progress in space technology especially in the field of satellite remote sensing applications during the past five decades. Satellite based sensors provide a repetitive and synoptic coverage of inaccessible / larger areas which generated a time series database useful in identification and mapping of environment and resources. These databases form a scientific tool for various stakeholders to device suitable strategies for management of coastal and marine resources. This chapter analyses the various applications of satellite remote sensing and numerical modelling on identification and mapping of mangroves, coral reefs, fishing and molluscan grounds in the coastal marine ecosystems with relevant case studies and illustrations. The mapping methods for mangroves explains the classification protocols, advantages in using different remote sensing techniques and the comparison of different mapping techniques. In case of reef mapping, the vulnerability mapping of reefs due to extreme events is also discussed. Fish movement in a dynamic environment and the mapping of these movements with the help of proxy indicators are also detailed. Molluscan mapping is done based on the biomass differences during different seasons and their physical attributes

Pasturelands as natural climate solutions: a socioecological study of tree carbon and beef production trade-offs

Forest restoration is the most effective natural climate solution, with the potential to sequester 37% of the carbon dioxide (CO2) needed to reach the Paris climate mitigation goal. Cattle pastures offer an underutilized opportunity to increase global forest restoration efforts, improve biodiversity, and maximize carbon storage through the adoption of management strategies that prioritize the incorporation of trees into pasturelands. However, remote estimations of tree carbon storage in pastoral systems have never been field-verified and their accuracy is unclear. Furthermore, the effect of increased trees on cattle production is understudied across biomes. Lastly, the restoration potential of these landscapes as a byproduct of tree carbon also remains to be studied. Therefore, the aims of this study were (i) compare past remote tree carbon estimations in pastureland systems to current field estimates to assess their accuracy, (ii) evaluate the effect of increasing tree carbon (MgC ha-1) on the pastoral stocking density (AU ha-1), (iii) quantify the woody species diversity (H’) within pastures, and (iv) compare findings between farms in temperate (n = 26) and tropical (n = 16) ecosystems. To accomplish these goals, two remote datasets of global tree carbon from Harris et al., 2021 and Chapman et al., 2020 were first acquired, while the current pastoral carbon storage in temperate forest ecosystems of Virginia, USA and dry tropical forest ecosystems of Los Santos, Panama was estimated with in-situ plots. Woody plant species were also quantified to determine diversity as a metric of ecological restoration potential within these systems. We also conducted IRB-approved interviews with landowners to better understand their motivations for tree incorporation in their systems. We found that Chapman et al., 2020 significantly overestimated the carbon storage of pasturelands in Los Santos, Panama, while underestimating carbon in Virginia (p \u3c 0.001). There was no difference in MgC ha-1 between tropical farms and temperate farms, but H’ (p \u3c 0.001) and stocking density (AU ha-1) were significantly higher in Los Santos, Panama (p = 0.003). Additionally, farms enrolled in conservation programs had lower stocking densities than those that practiced traditional management (p = 0.026), but no significant differences in H’ or MgC ha-1. There was also no effect of MgC ha-1 on stocking density, which suggests that pastures with more trees did not result in a decrease in beef production. Woody species diversity (H’) was positively associated with increasing MgC ha-1 (p \u3c 0.001), in Los Santos, but not in Virginia. Landowners had overall positive perceptions of trees in their systems, but some struggled to incorporate them due to financial and labor-related hurdles. These findings demonstrate the potential for pastures to increase above ground tree carbon and potentially woody species diversity without decreasing beef production. Moreover, such efforts support landscape restoration and offer potentially novel revenue streams for farmers through carbon credit programs. Lastly, we demonstrate the importance of taking a socio-ecological approach to restoration of human-dominated systems

Coastal and Marine Resource Condition Monitoring – Scoping Project

This pilot study investigated potential resource condition indicators, remote sensing, and ground truthing methodologies, for their use in long term monitoring of mangroves and intertidal mudflats in the Pilbara and Kimberley