Baseline Land Cover (Summer) - Sacramento-San Joaquin Delta - 2018 - Point Blue [ds3038]

This is one of 8 raster geotiff layers that make up the larger dataset "Baseline and projected future land use and land cover in the Sacramento-San Joaquin Delta", which represents recent (2018) and proposed or anticipated future (2050) land use and land cover in the Sacramento-San Joaquin Delta and the surrounding 10km. These layers were developed by Point Blue Conservation Science for a project funded through the Proposition 1 Delta Water Quality and Ecosystem Restoration Program administered by the California Department of Fish and Wildlife titled "Trade-offs and Co-benefits of Landscape Change Scenarios on Bird Communities and Ecosystem Services in the Sacramento-San Joaquin River Delta (Grant Agreement Number Q1996022). These data were used in the evaluation of net impacts of landscape change on multiple metrics including agricultural livelihoods, water quality (pesticide application rates), climate change resilience, and biodiversity support, to inform land management and conservation planning. The baseline land use and land cover classifications are based primarily on classification of imagery of the Delta in 2016 from the National Agriculture Imagery Program (NAIP) (ds2855), overlaid with more recent crop cover data based on imagery from 2018 (CDWR 2021). This primary baseline layer includes primary summer crops in the Delta, while an alternate version (baseline_win) includes winter crops. We also filled in a 10km buffer surrounding the Delta's boundary using classification of NAIP imagery for the Great Valley Ecoregion in 2009, 2012, and 2014 (ds2632), and manually identified tidal wetland and managed wetlands using other sources (Petrik et al. 2014; SFEI 2016). Original land cover classifications were grouped into major natural and agricultural land cover classes and subclasses using a combination of CWHR, NVCS, and DWR/LandIQ crop classifications. We considered the baseline data to represent land use and land cover in 2018.See Dybala et al. (In review-A) and Dybala et al. (In review-B) for additional details on the development, assumptions, limitations, and applications of these data.

Disclaimer: The State makes no claims, promises, or guarantees about the accuracy, completeness, reliability, or adequacy of these data and expressly disclaims liability for errors and omissions in these data. No warranty of any kind, implied, expressed, or statutory, including but not limited to the warranties of non-infringement of third party rights, title, merchantability, fitness for a particular purpose, and freedom from computer virus, is given with respect to these data.