Data and code from: Cultivation and dynamic cropping processes impart land-cover heterogeneity within agroecosystems: a metrics-based case study in the Yazoo-Mississippi Delta (USA)
This dataset contains data and code from the manuscript:
Heintzman, Lucas J., Nancy E. McIntyre, Eddy J. Langendoen, and Quentin D. Read. 2023. Cultivation and dynamic cropping processes impart land-cover heterogeneity within agroecosystems: a metrics-based case study in the Yazoo-Mississippi Delta (USA). *Landscape Ecology*, in revision. **Citation will be updated when MS is accepted.**
There are 14 rasters of land use and land cover data for the study region, in .tif format with associated auxiliary files, two shape files with county boundaries and study area extent, a CSV file with summary information derived from the rasters, and a Jupyter notebook containing Python code.
Data from: Not just crop or forest: building an integrated land cover map for agricultural and natural areas (tabular files)
To address the need for maps that characterize detailed land cover, including both agricultural and natural habitats, we combined two national datasets of land cover, the Landscape Fire and Resource Management Planning Tools (LANDFIRE) National Vegetation Classification (NVC) and United States Department of Agriculture, National Agricultural Statistics Service (USDA-NASS) Cropland Data Layer (CDL). Our workflow leveraged strengths of the NVC and the CDL to produce annual land-use rasters for 2012-2021.
Agricultural land use by field: Upper Mississippi River Basin 2010-2020
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Data from: Multiscale climatological albedo look-up maps derived from moderate resolution imaging spectroradiometer BRDF/albedo products
The dataset includes albedo look-up maps (LUMs) using a multiscale hierarchical approach based on moderate resolution imaging spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo products and Landsat imagery. Ten years (2001 to 2011) of MODIS BRDF/albedo products were used to generate global albedo climatology.
Agricultural land use by field: Nebraska 2010-2020
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Agricultural land use by field: Illinois 2010-2020
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Biodiversity, ecosystem services, and the socioeconomic sustainability of rural forest-based communities
This project involved three types of data: (1) secondary data of rural forested communities using US Census, National Land Cover Data (NLCD), and USGS public domain data; (2) key informant semi-structured interviews in 9 communities in four states; and (3) community resident surveys.
A dataset of spatiotemporally sampled MODIS Leaf Area Index with corresponding Landsat surface reflectance over the contiguous US
This dataset was built to assist a machine-learning-based approach for mapping LAI from 30m-resolution Landsat images across the contiguous US (CONUS). The data was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Version 6 LAI/FPAR, Landsat Collection 1 surface reflectance, and NLCD Land Cover datasets over 2006 – 2018 using Google Earth Engine.