Project Funding: 2016 - 2019

NRA: 2015 NASA: Land Cover / Land Use Change   

Funded by NASA

Abstract:
(1) Primary Island Sites (Hawaiian Islands, Galapagos Islands, Puerto Rico) will be characterized using an assembled social-ecological data set, including, population censuses, tourism data, household surveys, environmental data, local & community infrastructure data, and a blended satellite image stack populated by LANDSAT & MODIS imagery, but also SENTINEL, ASTER, HYPERION & ADVANCED LAND IMAGER data. Existing image archives will be consulted for all available imagery, including the USGS Global Visualization Viewer, USGS EarthExplorer, and NASA Earth Exchange web portals. The nominal periods of study are 1990, 1995, 2000, 2005, 2010 & 2015. (2) Published information will be distilled from LCLUC case studies for Primary & Secondary Island Sites (Fiji, Azores, Canary Islands, Madagascar, Seychelles, Tahiti) and for islands more generally. LCLUC classification schemes (e.g., USGS National Land Cover Database & NOAA C-CAP Program) will be examined and a suite of LCLUC classes selected that best represent island ecosystems, particularly, those that suggest a transition from natural to human systems (e.g., forest to urban & built-up) and from human to natural systems (e.g., reforestation of abandoned land). Our classification focus will be on urban & built up (low, medium, high intensity), forest (deciduous, evergreen, mixed), cultivated crops, pasture, agroforestry, grasslands, wetlands, open water, beaches, shrub/scrub, and barren. High spatial resolution imagery, e.g., Worldview-2, QuickBird, Google Earth Pro & Google Earth Engine images, will be used for calibration & validation. Using our defined LCLU classes, a suite of change-detections will be generated that represent from-to� transitions, with a focus on (1) intensification of urban & built-up, (2) rural to urban, (3) deforestation & reforestation, (4) agricultural extensification & land abandonment, (5) transitions among cultivated crops, pasture & agroforestry, and (6) coastal & interior island development and the transition of beaches, wetlands, forest, shrub/scrub, and open water. We will also track the fragmentation patterns and changes in vegetation & environmental indices. Further, we will construct LCLUC trajectories using derived sequences, focusing on the timing, magnitude, and stability/dynamism of LCLUC relative to the six transitions listed above. (3) Findings will be synthesized based mainly on models developed for the Primary Sites informed through statistical functions that link variables and rates of LCLUC documented in the literature. We will develop a Dynamic Systems Model that is sufficiently robust and capable of capturing the main social-ecological variations and dynamics of the drivers of LCLUC on the Primary Sites. We will then test the Model to see how well it represents the variation in the Primary Sites, including performing sensitivity analysis to assess model performance. The Dynamic Systems Model will also be tested through what if scenarios of change. (4) We will expand the degree to which the model can be applied in the Secondary Sites by compiling population censuses, tourism data, household surveys, environmental data, and fused satellite assets to assess LCLUC patterns and the drivers of change. We will secure archival satellite image data as done for our Primary Sites. We will apply the Dynamic Systems Model to the Secondary Sites with necessary modifications and test model performance using sensitivity analysis. (5) As further demonstration of the generalizability of our Dynamic Systems Model, we will develop and test our models using MODIS imagery and globally available & gridded population and socio-economic data maintained by (a) CIESEN, Columbia University, the GRUMP databases, (b) LandScan Global Data Set, Oak Ridge National Laboratory, (c) Global data sets including the Pacific Climate Information System, NASAs Earth Observing System Data & Information System, NOAAs Coastal Change Analysis Program.