A 2001–2015 Archive of Fractional Cover of Photosynthetic and Non-Photosynthetic Vegetation for Beijing and Tianjin Sandstorm Source Region

<p>The data cover land ranging from 38°50′ to 46°40′ N and from 109°30′ to 120°30′ E. The archive starts in January 2001 and ends in December 2015. It contains one raster layer per month for each of these variables:</p><p>Fractional cover of PV (%)</p><p>Fractional cover of NPV (%)</p><p>Fractional cover of bare soil (%)</p><p>The archive is managed in a Geographic Information System (GIS). All the layers are in the GeoTiff format. The valid data range spans from 0 to 100.The no data pixels are illustrated by 255.</p><p>The archive is organized in three large compressed files,one per variable. File names are according to the following conventions:<br></p><p>Characters 1–5: region name (btssr)</p><p>Characters 6–7: variable name (pv, np, or bs)</p><p>Characters 8–11: year (2001 to 2015)</p><p>Characters 12–13: month (01 to 12)</p> <p>For example, ‘btssrnp200508’ refers to the fractional cover of NPV in August 2005 for the BTSSR.<br></p

Calibration and Validation of Remotely Sensed Ground Cover Maps

Calibration and validation is essential in the development of remotely sensed fractional ground cover maps to ensure their reliability and provide users with confidence. Field measurements of fractional cover (FC) are typically collected through surveys where participants have the potential to introduce biases as they categorise ground cover. Environmental factors also have potential to influence the reliability of image-derived products. FC maps have been found to provide poor estimates of cover in arid regions of Australia, and it has been suggested that this may be due to soil colour. Further investigation is required to determine if soil colour influences satellite-derived FC products and there is scope to explore other methods of collecting field measurements in order to reduce errors. The aim of this thesis was to investigate methods of improving fractional ground cover mapping in Australia. The objectives were to (1) trial hyperspectral ground cover sampling in arid Australia by determining how spectral surveys and traditional sampling compare at the same scale and to compare these field methods to satellite-derived FC products, (2) examine observer consistency when classifying vegetation as photosynthetic or non-photosynthetic and to examine how spectral classification of vegetation compares to observer results, and (3) determine if the Australian MODIS FC product is influenced by soil colour. For objective one a sampling design suitable for the evaluation of coarse resolution imagery was developed. Sites were sampled collecting hyperspectral reflectance measurements and step-point observations of ground cover that were later compared to Australian MODIS and Landsat FC products. The results showed a strong relationship between the field sampling methods, that the Landsat FC product was strongly correlated to non-photosynthetic vegetation and soil and the MODIS product was strongly correlated to photosynthetic vegetation. This study demonstrated the hyperspectral field sampling’s improved objectivity, ease of use, and ability to produce results comparable to traditional transect measures. Objective two examined photographs and reflectance measurements of vegetation transitioning from 100% photosynthetic to 100% non-photosynthetic. Observers classified leaves as either photosynthetic or non-photosynthetic (as required in field fractional cover methods), while spectral unmixing was used to decompose the reflectance measurements into photosynthetic and non-photosynthetic proportions. At the extremes (≤ 25 % or ≥ 75 %) photosynthetic observers tended to agree and assigned the leaf to the correct category. However, for leaves in transition (> 25 % or < 75 % photosynthetic) decisions differed more widely and classifications showed little agreement with the spectral proportions of photosynthetic and non-photosynthetic vegetation. This study increased our understanding of the limitations of field data collected using traditional observation methods, of observer variation, and of when observer data may become unreliable. Objective three compared MODIS and TERN AusPlot field estimates of FC at 250 sites across Australia and examined the effect of soil colour (represented by Munsell hue) on the FC values. Overall, there was a significant difference between all 250 sites based on hue suggesting that soil colour has a significant effect on the MODIS product. This evaluation provided insights into the association of specific soil colours with bias in MODIS ground cover fractions and highlighted hues that are associated with under- or overestimation of MODIS FC. Future research may utilise this information to help develop methods of minimising the effects of soil colour in future FC products. This thesis has contributed toward efforts to improve the collection of ground cover measurements for the validation of remotely sensed products, using spectral transect surveys as an alternative to traditional surveys, for photosynthetic activity, provided insight into observer classification consistency and determined how observer-based classification and hyperspectral unmixing compare, and contributed to our understanding of the effects of soil colour on the MODIS FC product. This knowledge will allow informed consumption of the current MODIS FC product, and assist future efforts to calibrate and validate FC products ensuring end-users have reliable and consistent ground cover data for research and decision making.Thesis (Ph.D.) -- University of Adelaide, School of Biological Sciences, 202

Forest Recovery from Hurricane Disturbances: The Influence of Changing Climate

Hurricanes are a major disturbance to tropical forests. The forest structure and composition are affected by the immediate damages and mortality caused by the disturbance and altered by the subsequent recovery via species succession and competition. To understand the mortality and recovery, we use census observations at Bisley Experimental Watersheds (BEW) in Puerto Rico to study the mortality after hurricane Hugo in 1989 and after hurricane Maria in 2017 and the subsequent recovery of the forest after hurricane Hugo between 1989 and 2014 (the last census before hurricane Maria). We found that hurricane-induced mortality varied with species/plant functional types (PFTs) and stem sizes. Specifically, palms are wind-resistant and had the lowest mortality, followed by mid and late successional trees. Early successional trees had the highest mortality. Small stems were protected and had the lowest mortality compared to medium and large stems in a large-stem dominant forest, but they were exposed and had the highest mortality in a small-stem dominated forest. In the succession recovery of the forest after hurricane Hugo, palms had the lowest background mortality and the highest recruitment rate, which make them superior competitors in the forest. We implement a hurricane disturbance module, which accounts for both the immediate mortality and subsequent recovery of each PFT and stem size class, in the ecosystem demography model (ED2). We calibrate the model to properly represent the stem density, aboveground biomass, PFT composition and size structure of the forest in the 25 years of recovery from hurricane Hugo. Then we use the calibrated model to study the impact of 1) initial forest state, 2) climate conditions (e.g., temperature, precipitation, CO2 concentration, etc.), and 3) hurricane severity (frequency and intensity) on the recovery of forest biomass and composition. The simulation results show that a single hurricane disturbance on a forest with wind-resistant initial state will result in a higher aboveground biomass level after 100 years of recovery compared to a less wind-resistant initial state. PFT composition and size structure at recovery are not as dependent on initial state. However, frequent and intense hurricane disturbances in the future will decrease the aboveground biomass accumulation and alter the PFT composition. Specifically, frequent and intense hurricane disturbances will increase the abundance of palms and early successional trees but decrease the abundance of late successional trees. The effects will be enhanced with more frequent and intense hurricanes. Higher SSP-scenario (warmer and higher CO2 concentration) climates will enhance the aboveground biomass accumulation but will have smaller effects on the composition and structure of the forest in comparison to hurricane disturbances. The biomass accumulation from higher SSP-scenario climates cannot compensate for the biomass loss due to hurricane disturbances. In summary, we have demonstrated that 1) the state of the forest at the time of disturbance has effects on the recovery of the forest, especially on the biomass accumulation, but less effect on the composition and structure; 2) The severity of the hurricane disturbance has significant impacts on the biomass accumulation, composition and structure of the forest; 3) Climate change with higher temperature, humidity, and CO2 concentration will promote biomass, but not sufficiently to counteract biomass reduction from hurricane disturbances; 4) Palms will become more and more abundant in forests that are subject to frequent hurricane disturbances.Ph.D