Plant survival monitoring with UAVs and multispectral data in difficult access afforested areas

This is an Accepted Manuscript of an article published by Taylor & Francis in Geocarto International on 02 Oct 2018, available online: http://www.tandfonline.com/10.1080/10106049.2018.1508312Water supply devices enable afforestation in dry climates and on poor lands with generally high success rates. Previous survival analyses have been based on the direct observation of each individual plant in the field, which entails considerable effort and costs. This study provides a low-cost method to discriminate between live and dead plants in afforestations that can efficiently replace traditional field inspections through the use of UAVs equipped with RGB and NIR sensors. The method combines the use of a conventional camera with an identical camera modified to record the NIR channel. Survival analysis was performed with digital image processing techniques based on calculated indices associated with plant vigour and PCA-based decorrelation. The method yielded results with high global accuracy rates (~96.2%) with a minimum percentage of doubtful plants, even in young plantations (seedlings < 30 cm tall). The procedure could be particularly useful in hazardous areasThis work was supported by the Xunta de Galicia under the Grant “Financial aid for the consolidation and structure of competitive units of investigation in the universities of the University Galician System (2016-18)” [ED431B 2016/030, ED341D R2016/023] and the European Program Life+ [LIFE/ENV/ES/000447] “The Green Deserts: New planting techniques for tree cultivation in desertified environments to face Climate Change”.S

Uncovering Dryland Woody Dynamics Using Optical, Microwave, and Field Data—Prolonged Above-Average Rainfall Paradoxically Contributes to Woody Plant Die-Off in the Western Sahel

Dryland ecosystems are frequently struck by droughts. Yet, woody vegetation is often able to recover from mortality events once precipitation returns to pre-drought conditions. Climate change, however, may impact woody vegetation resilience due to more extreme and frequent droughts. Thus, better understanding how woody vegetation responds to drought events is essential. We used a phenology-based remote sensing approach coupled with field data to estimate the severity and recovery rates of a large scale die-off event that occurred in 2014&ndash;2015 in Senegal. Novel low (L-band) and high-frequency (Ku-band) passive microwave vegetation optical depth (VOD), and optical MODIS data, were used to estimate woody vegetation dynamics. The relative importance of soil, human-pressure, and before-drought vegetation dynamics influencing the woody vegetation response to the drought were assessed. The die-off in 2014&ndash;2015 represented the highest dry season VOD drop for the studied period (1989&ndash;2017), even though the 2014 drought was not as severe as the droughts in the 1980s and 1990s. The spatially explicit Die-off Severity Index derived in this study, at 500 m resolution, highlights woody plants mortality in the study area. Soil physical characteristics highly affected die-off severity and post-disturbance recovery, but pre-drought biomass accumulation (i.e., in areas that benefited from above-normal rainfall conditions before the 2014 drought) was the most important variable in explaining die-off severity. This study provides new evidence supporting a better understanding of the &ldquo;greening Sahel&rdquo;, suggesting that a sudden increase in woody vegetation biomass does not necessarily imply a stable ecosystem recovery from the droughts in the 1980s. Instead, prolonged above-normal rainfall conditions prior to a drought may result in the accumulation of woody biomass, creating the basis for potentially large-scale woody vegetation die-off events due to even moderate dry spells

Long-term patterns in remotely-sensed vegetation productivity for a transboundary conservation area in Southern Africa.

In the past century, researchers have observed changes in vegetation productivity and structure in savannas across the world. These changes, caused by shifts in precipitation patterns, fire patterns, soil nutrients, herbivory, and land management decisions, are important to understand because they affect availability of natural resources, which in turn affects the livelihoods of local populations. This study centers on the Kavango-Zambezi Transfrontier Conservation Area (KAZA), a transboundary conservation area that spans five countries in Southern Africa comprised of large areas of protected land. Using the Normalized-Difference Vegetation Index (NDVI), I tested a 35-year remotely-sensed time series for intra- and inter-annual vegetation patterns in KAZA between 1981 and 2015, including analyses for three communities in the region. A Mann- Kendall test for monotonic trends and a Sen’s Slope test were conducted to analyze inter-annual trends for significance and slope of change, respectively. Annual green-up time, the onset of the growing season, was also analyzed for spatial patterns. I found a positive overall trend of greening, as well as spatially clustered patterns of greening and browning across the study region, with sub-study area variation discussed at the community level. Annual growing season onset green-up patterns also varied, appearing to be spatially clustered across the region. The patterns found here have implications for stakeholders at the local and regional levels and will continue to develop as the region continues to face social and environmental changes, thus, continued monitoring is advised

Grazing and Climate Effects on High Elevation Meadow Resources

Semi-arid rangelands cover roughly 41% of the Earth’s land surface, and house more than 38% of the human global population. The Greater sage-grouse (Centrocercus urophasianus) has commonly been used as an umbrella species for restoration of sagebrush ecosystems in rangelands, due to its status as an indicator of overall rangeland health. Scarce mesic resources may lead to an energetic bottleneck for juvenile sage grouse, limiting fitness and survival rates. Mesic and ground-water dependent ecosystems found in the Great Basin of North America are heavily utilized by livestock and wildlife throughout the year. It is important for land managers to understand how intensity and timing of grazing affect the temporal availability of mesic commodities utilized by species like sage-grouse. This dissertation quantifies changes in the timing of availability of mesic sage-grouse resources across grazing and climatic gradients in high-elevation meadows. The methods include both on the ground and remotely sensed tools, and the correlations between them are assessed. The results suggest that field determined phenology, phenocam Green Chromatic Coordinate (GCC), Phenocam Normalized Difference Vegetation Index (NDVI), and Landsat NDVI are all highly correlated, with slight de-coupling occurring at the end of the growing season. Timing of growth varied in these ecosystems depending on yearly precipitation and vegetative type. Arthropod taxa abundance responded differently to grazing management and environmental variables in these meadow communities. Coleoptera abundance during peak sage-grouse usage periods had an increase of roughly 40% in some meadows with increased grazing intensity, while Formicidae abundance saw a 22% decrease. Near-surface cameras had varied success with predicting peak insect abundance levels. Sage grouse usage of the meadows was highly linked to growth seasons of vegetation, with slight decoupling occurring with growth seasons derived from phenocam GCC in drier years. Little correlation was seen between peak sage grouse usage of the meadows and peak capture rates of arthropods, this was true for all insect groups (Coleoptera, Formicidae, and Lepidoptera)

Grazing and Climate Effects on High Elevation Meadow Resources

Semi-arid rangelands cover roughly 41% of the Earth’s land surface, and house more than 38% of the human global population. The Greater sage-grouse (Centrocercus urophasianus) has commonly been used as an umbrella species for restoration of sagebrush ecosystems in rangelands, due to its status as an indicator of overall rangeland health. Scarce mesic resources may lead to an energetic bottleneck for juvenile sage grouse, limiting fitness and survival rates. Mesic and ground-water dependent ecosystems found in the Great Basin of North America are heavily utilized by livestock and wildlife throughout the year. It is important for land managers to understand how intensity and timing of grazing affect the temporal availability of mesic commodities utilized by species like sage-grouse. This dissertation quantifies changes in the timing of availability of mesic sage-grouse resources across grazing and climatic gradients in high-elevation meadows. The methods include both on the ground and remotely sensed tools, and the correlations between them are assessed. The results suggest that field determined phenology, phenocam Green Chromatic Coordinate (GCC), Phenocam Normalized Difference Vegetation Index (NDVI), and Landsat NDVI are all highly correlated, with slight de-coupling occurring at the end of the growing season. Timing of growth varied in these ecosystems depending on yearly precipitation and vegetative type. Arthropod taxa abundance responded differently to grazing management and environmental variables in these meadow communities. Coleoptera abundance during peak sage-grouse usage periods had an increase of roughly 40% in some meadows with increased grazing intensity, while Formicidae abundance saw a 22% decrease. Near-surface cameras had varied success with predicting peak insect abundance levels. Sage grouse usage of the meadows was highly linked to growth seasons of vegetation, with slight decoupling occurring with growth seasons derived from phenocam GCC in drier years. Little correlation was seen between peak sage grouse usage of the meadows and peak capture rates of arthropods, this was true for all insect groups (Coleoptera, Formicidae, and Lepidoptera)

Estimating live fuel moisture content in Oklahoma plants

Live fuel moisture content (LFM) is an important variable in fire danger rating systems. LFM collection is time and resource intensive and plant water relations vary within and between species. Consequently, the best approach for estimating LFM is unknown. Few studies have investigated LFM in the state of Oklahoma, and current estimates of LFM have not been validated. The objectives of this study were to evaluate the use of environmental and remote sensing proxies for estimating LFM in Oklahoma plants. I found that LFM can be accurately estimated using either hyperspectral leaf-level reflectance or environmental proxies. My analysis of several remote sensing vegetation indices identified the Water Index and VIgreen as the best suited indices for approximating LFM. Using functional group, photoperiod, vapor pressure deficit, and rainfall I was able to estimate LFM in Oklahoma plant communities. In addition to these findings, I identified a need to reevaluate current methods for estimating LFM. By advancing our understanding of LFM and how best to predict it, my results can be used in fire danger rating systems to protect lives and preserve natural resources

Remote sensing environmental change in southern African savannahs : a case study of Namibia

Savannah biomes cover a fifth of Earth’s surface, harbour many of the world’s most iconic species and most of its livestock and rangeland, while sustaining the livelihoods of an important proportion of its human population. They provide essential ecosystem services and functions, ranging from forest, grazing and water resources, to global climate regulation and carbon sequestration. However, savannahs are highly sensitive to human activities and climate change. Across sub-Saharan Africa, climatic shifts, destructive wars and increasing anthropogenic disturbances in the form of agricultural intensification and urbanization, have resulted in widespread land degradation and loss of ecosystem services. Yet, these threatened ecosystems are some of the least studied or protected, and hence should be given high conservation priority. Importantly, the scale of land degradation has not been fully explored, thereby comprising an important knowledge gap in our understanding of ecosystem services and processes, and effectively impeding conservation and management of these biodiversity hotspots. The primary drivers of land degradation include deforestation, triggered by the increasing need for urban and arable land, and concurrently, shrub encroachment, a process in which the herbaceous layer, a defining characteristic of savannahs, is replaced with hardy shrubs. These processes have significant repercussions on ecosystem service provision, both locally and globally, although the extents, drivers and impacts of either remain poorly quantified and understood. Additionally, regional aridification anticipated under climate change, will lead to important shifts in vegetation composition, amplified warming and reduced carbon sequestration. Together with a growing human population, these processes are expected to compound the risk of land degradation, thus further impacting key ecosystem services. Namibia is undergoing significant environmental and socio-economic changes. The most pervasive change processes affecting its savannahs are deforestation, degradation and shrub encroachment. Yet, the extent and drivers of such change processes are not comprehensively quantified, nor are the implications for rural livelihoods, sustainable land management, the carbon cycle, climate and conservation fully explored. This is partly due to the complexities of mapping vegetation changes with satellite data in savannahs. They are naturally spatially and temporally variable owing to erratic rainfall, divergent plant functional type phenologies and extensive anthropogenic impacts such as fire and grazing. Accordingly, this thesis aims to (i) quantify distinct vegetation change processes across Namibia, and (ii) develop methodologies to overcome limitations inherent in savannah mapping. Multi-sensor satellite data spanning a range of spatial, temporal and spectral resolutions are integrated with field datasets to achieve these aims, which are addressed in four journal articles. Chapters 1 and 2 are introductory. Chapter 3 exploits the Landsat archive to track changes in land cover classes over five decades throughout the Namibian Kalahari woodlands. The approach addresses issues implicit in change detection of savannahs by capturing the distinct phenological phases of woody vegetation and integrating multi-sensor, multi-source data. Vegetation extent was found to have decreased due to urbanization and small-scale arable farming. An assessment of the limitations leads to Chapter 4, which elaborates on the previous chapter by quantifying aboveground biomass changes associated with deforestation and shrub encroachment. The approach centres on fusing multiple satellite datasets, each acting as a proxy for distinct vegetation properties, with calibration/validation data consisting of concurrent field and LiDAR measurements. Biomass losses predominate, demonstrating the contribution of land management to ecosystem carbon changes. To identify whether biomass is declining across the country, Chapter 5 focuses on regional, moderate spatial resolution time-series analyses. Phenological metrics extracted from MODIS data are used to model observed fractional woody vegetation cover, a proxy for biomass. Trends in modelled fractional woody cover are then evaluated in relation to the predominant land-uses and precipitation. Negative trends slightly outweighed positive trends, with decreases arising largely in protected, urban and communal areas. Since precipitation is a fundamental control on vegetation, Chapter 6 investigates its relation to NDVI, by assessing to what extent observed trends in vegetation cover are driven by rainfall. NDVI is modelled as a function of precipitation, with residuals assumed to describe the fraction of NDVI not explained by rainfall. Mean annual rainfall and rainfall amplitude show a positive trend, although extensive “greening” is unrelated to rainfall. NDVI amplitude, used as a proxy for vegetation density, indicates a widespread shift to a denser condition. In Chapter 7, trend analysis is applied to a Landsat time-series to overcome spatial and temporal limitations characteristic of the previous approaches. Results, together with those of the previous chapters, are synthesized and a synopsis of the main findings is presented. Vegetation loss is predominantly caused by demand for urban and arable land. Greening trends are attributed to shrub encroachment and to a lesser extent conservation laws, agroforestry and rangeland management, with precipitation presenting little influence. Despite prevalent greening, degradation processes associated with shrub encroachment, including soil erosion, are likely to be widespread. Deforestation occurs locally while shrub encroachment occurs regionally. This thesis successfully integrates multi-source data to map, measure and monitor distinct change processes across scales

Patrones espaciales y temporales de la productividad primaria neta aérea herbácea y leñosa en el Chaco Árido (Argentina)

En esta tesis se propuso describir la variación espacio-temporal de la productividad primaria neta aérea (PPNA) de tipos funcionales herbáceos y leñosos a escalas predial y regional. Para ello fue necesario generar herramientas metodológicas que permitan discriminar tipos funcionales herbáceos y leñosos a partir de sensores remotos. La propuesta metodológica se sustentó en el uso de sensores remotos satelitales, que permitieran cubrir amplias superficies, con un grano espacial adecuado (pixel = 250 m) y una alta frecuencia temporal (16 días) desde el año 2000, complementada con seguimiento espectral de plantas individuales con radiómetro de mano. Se utilizó el índice de vegetación de diferencia normalizada (IVN), un estimador de la PPNA. La marcha estacional del IVN fue diferente entre tipos funcionales leñosos y herbáceos. Tanto los árboles como los arbustos presentaron períodos de crecimiento mayores a los pastos, más estables (menor variabilidad) dentro de cada período de crecimiento y entre períodos. La desagregación de series de tiempo del IVN MODIS en sus componentes leñoso (L) y herbáceo (H) permitió generar modelos de estimación satelital de la PPNA leñosa (PPNAL) y herbácea (PPNAH) con aceptable ajuste. Las estimaciones de PPNAH y PPNAL utilizando el modelo de eficiencia en el uso de la radiación (EUR), a partir del IVN MODIS, permitió describir satisfactoriamente patrones espacio – temporales de PPNAH y PPNAL a escala regional y predial en la región del Chaco Árido. Finalmente, se propusieron bases metodológicas para hacer seguimiento y planificación forrajera a escala predial y valoración de procesos de desertificación a escala regional, en ambientes donde conviven especies herbáceas y leñosas