Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment : Advantages and Limitations

In spite of considerable efforts to monitor global vegetation, biomass quantification in drylands is still a major challenge due to low spectral resolution and considerable background effects. Hence, this study examines the potential of the space-borne hyperspectral Hyperion sensor compared to the multispectral Landsat OLI sensor in predicting dwarf shrub biomass in an arid region characterized by challenging conditions for satellite-based analysis: The Eastern Pamirs of Tajikistan. We calculated vegetation indices for all available wavelengths of both sensors, correlated these indices with field-mapped biomass while considering the multiple comparison problem, and assessed the predictive performance of single-variable linear models constructed with data from each of the sensors. Results showed an increased performance of the hyperspectral sensor and the particular suitability of indices capturing the short-wave infrared spectral region in dwarf shrub biomass prediction. Performance was considerably poorer in the area with less vegetation cover. Furthermore, spatial transferability of vegetation indices was not feasible in this region, underlining the importance of repeated model building. This study indicates that upcoming space-borne hyperspectral sensors increase the performance of biomass prediction in the world’s arid environments

Modeling β Diversity and Simpson’s Index Using Hyperion Reflectance in Vansda National Park, Gujarat

Global biodiversity is under threat due to increasing anthropogenic activities. Pressure on biodiversity is immense especially in rapidly developing countries like India.  In the present study, an attempt has been made to establish accurate relationships between Hyperion (EO1) reflectance spectra and measured β diversity index and Simpson’s index of the tropical moist deciduous forest of the study area. Developed accurate models can help in mapping and assessment of diversity at larger spatial scales. The efficiency of statistical modeling techniques including Partial Least Square (PLS) regression and Multiple Linear Regression (MLR), is demonstrated in this study (with maximum R2 of 0.74 and 0.73 for PLS and MLR respectively). A vegetation index (SR 1457/933) is introduced for β diversity estimation, yielding exceptional accuracy in model development and validation (with a maximum R2 of 0.63)

Utility of Satellite and Aerial Images for Quantification of Canopy Cover and Infilling Rates of the Invasive Woody Species Honey Mesquite (Prosopis Glandulosa) on Rangeland

Woody plant encroachment into grasslands and rangelands is a world-wide phenomenon but detailed descriptions of changes in geographical distribution and infilling rates have not been well documented at large land scales. Remote sensing with either aerial or satellite images may provide a rapid means for accomplishing this task. Our objective was to compare the accuracy and utility of two types of images with contrasting spatial resolutions (1-m aerial and 30-m satellite) for classifying woody and herbaceous canopy cover and determining woody infilling rates in a large area of rangeland (800 km<sup>2</sup>) in north Texas that has been invaded by honey mesquite (<em>Prosopis glandulosa</em>). Accuracy assessment revealed that the overall accuracies for the classification of four land cover types (mesquite, grass, bare ground and other) were 94 and 87% with kappa coefficients of 0.89 and 0.77 for the 1-m and 30-m images, respectively. Over the entire area, the 30-m image over-estimated mesquite canopy cover by 9 percentage units (10 <em>vs.</em> 19%) and underestimated grass canopy cover by the same amount when compared to the 1-m image. The 30-m resolution image typically overestimated mesquite canopy cover within 225 4-ha sub-cells that contained a range of mesquite covers (1–70%) when compared to the 1-m image classification and was not suitable for quantifying infilling rates of this native invasive species. Documenting woody and non-woody canopy cover on large land areas is important for developing integrated, regional-scale management strategies for rangeland and grassland regions that have been invaded by woody plants

Determinants of woody encroachment and cover in African savannas

Savanna ecosystems are an integral part of the African landscape and sustain the livelihoods of millions of people. Woody encroachment in savannas is a widespread phenomenon but its causes are widely debated. We review the extensive literature on woody encroachment to help improve understanding of the possible causes and to highlight where and how future scientific efforts to fully understand these causes should be focused. Rainfall is the most important determinant of maximum woody cover across Africa, but fire and herbivory interact to reduce woody cover below the maximum at many locations. We postulate that woody encroachment is most likely driven by CO2 enrichment and propose a two-system conceptual framework, whereby mechanisms of woody encroachment differ depending on whether the savanna is a wet or dry system. In dry savannas, the increased water-use efficiency in plants relaxes precipitation-driven constraints and increases woody growth. In wet savannas, the increase of carbon allocation to tree roots results in faster recovery rates after disturbance and a greater likelihood of reaching sexual maturity. Our proposed framework can be tested using a mixture of experimental and earth observational techniques. At a local level, changes in precipitation, burning regimes or herbivory could be driving woody encroachment, but are unlikely to be the explanation of this continent-wide phenomenon

Camelthorn and blackthorn trees provide important resources for southern pied babblers (Turdoides bicolor) in the Kalahari

SUPPLEMENTARY MATERIAL : FIGURE S1. Southern Pied Babblers Turdoides bicolor used intermediate height branches, avoiding particularly low or particularly high branches. FIGURE S2. Southern Pied Babblers Turdoides bicolor typically build their nests (a) within ~300 cm of the main tree trunk and (b) away from the canopy edge. FIGURE S3. Southern Pied Babblers Turdoides bicolor nested in exposed locations with high transmission coefficients (a) and avoided building nests with north-westerly orientations (b). Fledged nests are shown in black and failed nests in grey. TABLE S1. Mean Ivlev's electivity index value for selectivity (preference or avoidance) of the different Kalahari branch heights used for nesting by Southern Pied Babblers Turdoides bicolor.DATA AVAILABILITY STATEMENT : The data underlying all analyses presented in this study are archived at the University of Cape Town's open access institutional data repository, ZivaHub (a figshare platform), where they are publicly available (DOI: https://doi.org/10.25375/uct.20444610).In the southern Kalahari Desert, cooperatively breeding Southern Pied Babblers Turdoides bicolor frequently build their nests and forage in camelthorn trees Vachellia erioloba, a keystone species in the region, and blackthorn trees Senegalia mellifera, a widespread early successional shrub. Using Ivlev's electivity indices (Ei), we show that Southern Pied Babblers preferentially nest in camelthorn trees and preferentially forage in or under camelthorn and blackthorn trees. Southern Pied Babblers primarily forage on the ground; however, they will make use of arboreal resources when these are available. We observed the birds spending the highest proportion of foraging time off the ground during October, when breeding is also most common, compared with all other months within the austral summer breeding season. They are most likely to be observed foraging in camelthorn trees earlier in the breeding season and blackthorn trees later in the breeding season. We demonstrate that Southern Pied Babblers have a strong relationship with camelthorn trees, in which they prefer to both nest and forage. We highlight the importance of protecting camelthorn trees, a keystone species in the region, as part of the conservation and management of endemic Kalahari fauna such as the Southern Pied Babbler. In addition to contributing to the literature on keystone species, our observations raise questions about the ways in which avian reproduction in the arid zone could be decoupled from rainfall via the phenology of deep-rooted tree species.The British Ornithologists' Union, the Oppenheimer Memorial Trust, the National Research Foundation of South Africa, the Australian Research Council, the University of Cape Town and the DSI-NRF Centre of Excellence at the FitzPatrick Institute of African Ornithology.https://onlinelibrary.wiley.com/journal/1474919xhj2024Zoology and EntomologySDG-15:Life on lan

Genetic constraints on temporal variation of airborne reflectance spectra and their uncertainties over a temperate forest

Remote sensing enhances large-scale biodiversity monitoring by overcoming temporal and spatial limitations of ground-based measurements and allows assessment of multiple plant traits simultaneously. The total set of traits and their variation over time is specific for each individual and can reveal information about the genetic composition of forest communities. Measuring trait variation among individuals of one species continuously across space and time is a key component in monitoring genetic diversity but difficult to achieve with ground-based methods. Remote sensing approaches using imaging spectroscopy can provide high spectral, spatial, and temporal coverage to advance the monitoring of genetic diversity, if sufficient relation between spectral and genetic information can be established. We assessed reflectance spectra from individual Fagus sylvatica L. (European beech) trees acquired across eleven years from 69 flights of the Airborne Prism Experiment (APEX) above the same temperate forest in Switzerland. We derived reflectance spectra of 68 canopy trees and correlated differences in these spectra with genetic differences derived from microsatellite markers among the 68 individuals. We calculated these correlations for different points in time, wavelength regions and relative differences between wavelength regions. High correlations indicate high spectral-genetic similarities. We then tested the influence of environmental variables obtained at temporal scales from days to years on spectral-genetic similarities. We performed an uncertainty propagation of radiance measurements to provide a quality indicator for these correlations. We observed that genetically similar individuals had more similar reflectance spectra, but this varied between wavelength regions and across environmental variables. The short-wave infrared regions of the spectrum, influenced by water absorption, seemed to provide information on the population genetic structure at high temperatures, whereas the visible part of the spectrum, and the near-infrared region affected by scattering properties of tree canopies, showed more consistent patterns with genetic structure across longer time scales. Correlations of genetic similarity with reflectance spectra similarity were easier to detect when investigating relative differences between spectral bands (maximum correlation: 0.40) than reflectance data (maximum correlation: 0.33). Incorporating uncertainties of spectral measurements yielded improvements of spectral-genetic similarities of 36% and 20% for analyses based on single spectral bands, and relative differences between spectral bands, respectively. This study highlights the potential of dense multi-temporal airborne imaging spectroscopy data to detect the genetic structure of forest communities. We suggest that the observed temporal trajectories of reflectance spectra indicate physiological and possibly genetic constraints on plant responses to environmental change

Using sentinel-1 and sentinel-2 time series for slangbos mapping in the free state province, South Africa

Increasing woody cover and overgrazing in semi-arid ecosystems are known to be the major factors driving land degradation. This study focuses on mapping the distribution of the slangbos shrub (Seriphium plumosum) in a test region in the Free State Province of South Africa. The goal of this study is to monitor the slangbos encroachment on cultivated land by synergistically combining Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Sentinel-2) Earth observation information. Both optical and radar satellite data are sensitive to different vegetation properties and surface scattering or reflection mechanisms caused by the specific sensor characteristics. We used a supervised random forest classification to predict slangbos encroachment for each individual crop year between 2015 and 2020. Training data were derived based on expert knowledge and in situ information from the Department of Agriculture, Land Reform and Rural Development (DALRRD). We found that the Sentinel-1 VH (cross-polarization) and Sentinel-2 SAVI (Soil Adjusted Vegetation Index) time series information have the highest importance for the random forest classifier among all input parameters. The modelling results confirm the in situ observations that pastures are most affected by slangbos encroachment. The estimation of the model accuracy was accomplished via spatial cross-validation (SpCV) and resulted in a classification precision of around 80% for the slangbos class within each time step

Review of Methodologies for Land Degradation Neutrality Baselines: Sub-National case studies from Costa Rica and Namibia

The objective of this report is to identify entry points and challenges for subnational LDN baselines in order to inform subnational planning processes as potential vehicle for the implementation of LDN targets on the ground. For this purpose two focus regions were chosen within two of the countries – namely Namibia and Costa Rica – that participated in the first LDN pilot phase. The focus areas in Namibia and Costa Rica are the regions of Otjozondjupa and Rio Jesus Maria watershed respectively. Both Namibia and Costa Rica provide interesting case studies given the differences in types of land degradation, national capacities, and land resources

Advancements in the satellite sensing of the impacts of climate and variability on bush encroachment in savannah rangelands

An increase in shrubs or woody species is likely, directly or indirectly, to significantly affect rural livelihoods, wildlife/livestock productivity and conservation efforts. Poor and inappropriate land use management practices have resulted in rangeland degradation, particularly in semi-arid regions, and this has amplified the bush encroachment rate in many African countries, particularly in key savannah rangelands. The rate of encroachment is also perceived to be connected to other environmental factors, such as climate change, fire and rainfall variability, which may influence the structure and density of the shrubs (woody plants), when compared to uncontrolled grazing. Remote sensing has provided robust data for global studies on both bush encroachment and climate variability over multiple decades, and these data have complemented the local and regional evidence and process studies. This paper thus provides a detailed review of the advancements in the use of remote sensing for the monitoring of bush encroachment on the African continent, which is fuelled by climate variability in the rangeland areas

Mapping the remnant KwaZulu-Natal sandstone sourveld grass patches in the Ethekwini Municipality using a high resolution multispectral sensor.

Master of Science in the School of Agriculture, Earth and Environmental Sciences University of KwaZulu-Natal, Pietermaritzburg 2015.The indigenous KwaZulu-Natal sandstone sourveld (KZN SS) grassland is highly endemic and species-rich, yet critically endangered and poorly conserved. Ecological threats to this grassland are further exacerbated by the occurrence of woody plant encroachment, a form of degradation that has severe negative environmental and economic consequences. In this regard, understanding the distribution of the KZN SS fragments is critical for implementing conservation and management strategies. Advances in remote sensing technologies allow for accurate and precise mapping, hence the aim of this study is to identify the remnants of the KZN SS within the eThekwini Municipality using high resolution multispectral RapidEye data. The first part of this research seeks to assess the capability of RapidEye satellite imagery in mapping the indigenous KZN SS using support vector machines (SVM) and maximum likelihood (ML) classifiers. Although both techniques were successful in mapping the KZN SS, results show that ML was slightly outperformed by SVM, which yielded an overall accuracy of 74.4%. In addition, SVM were more accurate in distinguishing the KZN SS class with a score of 74.4%, compared to that of ML, namely 72.1%. The study underscores the importance of high resolution RapidEye data in detecting and mapping the remaining fragments of the KZN SS within the eThekwini Municipality. The second part of this research zoomed into discriminating between indigenous and alien woody plant encroachment within the KZN SS. The random forest (RF) algorithm was applied to the image and successfully mapped the two types of vegetation with an overall accuracy of 86%. In addition, an overall accuracy of 74% was obtained in estimating the five dominant tree species within the two classes. The results obtained highlight the potential of new generation RapidEye satellite data in combination with new advanced machine learning techniques in predicting the distribution of woody cover in a grassland ecosystem. Overall, this study successfully mapped the KZN SS patches, as well as bush encroachment patches. The strategic bands in the new generation RapidEye image were critical in species mapping