The 2005 Kansas Land Cover Patterns (KLCP) Mapping Initiative was a two-phase mapping endeavor that occurred over a three-year period (2007-2009). Note that while the processing occurred during the 2207-2009 period, all satellite data used in the project was acquired in 2005. Concurrent with mapping the state of Kansas, the Kansas River Watershed was also mapped. The Kansas River Watershed extends into southern Nebraska and includes a portion of eastern Colorado. During Phase I a Modified Level I map was produced. In Phase II a series of maps, Modified Level II through IV, were produced. All KLCP 2005 map products were produced at four spatial extents: the state of Kansas plus a 300 meter buffer, a DEM-derived watershed boundary of the Kansas River, the Kansas River watershed boundary plus a 1,000 meter buffer, and a combined dataset of the state of Kansas plus 300 meter buffer and the watershed plus 1,000 meter buffer.These extents are annotated in the file names with the extentions k, w, wb, and kwb respectively.

The goal of Phase II was to map subclasses for grassland and cropland, classes which were mapped during Phase I. For the Level II map, cool- and warm-season grasslands were mapped along with Spring Crop, Summer Crop, Alfalfa, Fallow, and Double-Crop classes. For the Level III map, the Summer Crop subclasses Corn, Soybean, and Sorghum were mapped, and the Spring Crop class was reassigned to Winter Wheat. In the Level IV map, irrigation status was mapped and added to the Level III crop type map.The Kansas Land Cover Patterns Level IV map contains twenty-four land use/land cover classes and has a positional accuracy and spatial resolution appropriate for producing 1:50,000 scale maps. The minimum map unit (MMU) varies by land cover class and ranges from 0.22 to 5.12 acres.

In general, the mapping methodology used a hybrid, hierarchical classification of multi-temporal, multi-resolution imagery to develop modified Anderson Level II through Anderson Level IV land cover maps of the Kansas River Watershed and the State of Kansas. More specifically, multi-seasonal Landsat Thematic Mapper (TM) imagery from the 2004 and 2005 growing season was used to map the grassland subclasses (cool- and warm-season grasslands). while MODIS NDVI time-series imagery from the 2005 growing season was used to map cropland subclasses.

The land use/land cover classes in the Level IV map are coded hierarchically to allow aggregation of land use and land cover classes as needed by the end-user. For example, a user can aggregate the Level IV map classes to a Level III classification by ignoring or eliminating the last digit of each land use/land cover class. Likewise, a Level II and Level I map can be created from the Level IV map by eliminating the last two and three digits, respectively, from each Level IV land use/land cover class.

A formal accuracy assessment found the Level II, Level III, and Level IV maps to have overall accuracy levels of 86.3%, 82.0%, and 74.3%, respectively. User and Producer (per-class errors of commission and omission) accuracies vary by land cover class and users are encouraged to reference the reported accuracy levels in the final report and/or metadata when using the Kansas Land Cover Patterns map series. Digital versions of the map, metadata, and accuracy assessment can be accessed from the Data Access Support Center (http://www.kansasgis.org/) or the Kansas Applied Remote Sensing Program (http://www.kars.ku.edu/).

This database was developed as part of the Core Database for the State of Kansas. It is suited for county-level and watershed-level analysis that involve land use and land cover.

[Summary provided by the Kansas Applied Remote Sensing, KARS, at the Kansas Biological Survey.]

Date of Images:9/29/2022, 10/2/2022, 10/3/2022, 10/4/2022Date of Next Image:N/ASummary:RADARSAT-2 and MSFC Sentinel-1:Scientists at NASA's Marshall Space Flight Center created these water extents on September 29, 2022 using the RADARSAT-2 Synthetic Aperture Radar (SAR) instrument. These images can be used to see where open water is visible at the time of the satellite overpass. This product shows all water detected and differentiates between normal water areas and some flooded areas. This product was classified using the USDA Crop Data Layer for 2021. It's important to note that all flooded areas may not be captured do to the sensors limitations of not being able to "see" through vegetation and buildings. To determine where additional flooding may have occurred, combine this layer with other data sets.ARIA Flood Proxy Map:This Flood Proxy Map (FPM) depicts areas that are likely flooded in Florida due to Hurricane Ian. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (9/30/2021) and after (10/2/2022) the event.Dartmouth Flood Observatory at the University of Colorado and NASA GSFC PlanetScope, Sentinel-1, and MODIS:Potentially flooded area created using PlanetScope imagery from October 2, 2022, October 3, 2022, and October 4, 2022 using a beta PlanetScope Flood Mapping system created in partnership between NASA GSFC and Dartmouth Flood Observatory at the University of Colorado.Potentially flooded area created using Sentinel-1 SAR data from October 2, 2022. The product is processed by the Dartmouth Flood Observatory at the University of Colorado, from Copernicus/European Space Agency Sentinel 1 SAR data. The NASA Earth Sciences Program provided funding to the University for Colorado for this work.Potentially flooded area created using MODIS data from September 30, 2022, October 2, 2022, and October 3, 2022. The product is processed by the Dartmouth Flood Observatory at the University of Colorado, MODIS instrument on the Terra and Aqua satellites. The NASA Earth Sciences Program provided funding to the University for Colorado for this work.Suggested Use:RADARSAT-2 and MSFC Sentinel-1:This product shows water that is detected by the sensor with different colors indicating different land cover/land use classifications from the USDA Crop Data Layer for 2021 that appear to have water and are potentially flooded.Blue (1): Known WaterRed (2): Anomalous WaterGreen (3): Flooded WetlandsBrown (4): Flooded CroplandsPurple (5): Potentially Flooded Developed Areas (Low Confidence)(0): No DataARIA Flood Proxy Map:Dark red pixels indicate areas that are likely flooded.This flood proxy map should be used as a guide to identify areas that are likely flooded, and is less reliable over urban and vegetated areas.Caveats: the majority of developed areas were filtered out due the capabilities of the sensor to detect urban flooding. As a result, these images may not detect all flooding and some potentially flooded developed areas could be inaccurate.Dartmouth Flood Observatory at the University of Colorado and NASA GSFC PlanetScope, Sentinel-1, and MODIS:In some cases, responders need this information only during the event. In many others, "building back better" requires accurate knowledge of what land areas were flooded, and also how large the event was compared to previous events. Input from disaster responders, flood risk analysts, and all others seeking information of what land was flooded during major events is welcomed. In many cases, Dartmouth Flood Observatory can produce information products tailored to end user GIS systems and analysis objectives. Write to Robert.Brakenridge@Colorado.edu or Albert.Kettner@Colorado.eduSatellite/Sensor:RADARSAT-2 Synthetic Aperture Radar (SAR)Copernicus Sentinel-1 Synthetic Aperture Radar (SAR)PlanetScopeMODISResolution:PlanetScope: 3 metersRADARSAT-2: ~20 metersSentinel-1: 30 metersMODIS: 250 metersCredits:NASA Disasters Program, Dartmouth Flood Observatory at the University of Colorado, NASA MSFC, NASA GSFCRADARSAT-2: This service contains modified RADARSAT-2 data, collected through Hazards Data Distribution System (HDDS)-USGS; post-processing and data product development performed by NASA Marshall Space Flight Center. RADARSAT-2 Data and Products © Maxar Technologies Ltd. (2022) - All Rights Reserved. RADARSAT is an official mark of the Canadian Space Agency.Sentinel-1: Sentinel data used in this derived product, contains modified Copernicus Sentinel data (2022), processed by ESA, Alaska Satellite Facility, NASA Marshall Space Flight CenterThe FPM contains modified Copernicus Sentinel data (2021-2022), processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA team. Part of the funding was provided by NASA's Earth Applied Sciences Disasters Program.PlanetScope: Includes copyrighted material of Planet Labs PBC. All rights reserved.Esri REST Endpoint:See URL section on the right side of page.WMS Endpoint: https://maps.disasters.nasa.gov/ags04/services/hurricane_ian_2022/water_extents/MapServer/WMSServer Data Download: DFO PlanetScope (flood extent): https://maps.disasters.nasa.gov/download/gis_products/event_specific/2022/hurricane_ian_2022/planet/dfo_gsfc/ DFO Sentinel 1: https://maps.disasters.nasa.gov/download/gis_products/event_specific/2022/hurricane_ian_2022/sentinel1/dfo/ DFO MODIS: https://maps.disasters.nasa.gov/download/gis_products/event_specific/2022/hurricane_ian_2022/modis/ Radarsat 2: https://maps.disasters.nasa.gov/download/gis_products/event_specific/2022/hurricane_ian_2022/radarsat2/ ARIA FPM: https://maps.disasters.nasa.gov/download/gis_products/event_specific/2022/hurricane_ian_2022/aria/ MSFC Sentinel-1: https://maps.disasters.nasa.gov/download/gis_products/event_specific/2022/hurricane_ian_2022/sentinel1/

The purpose of this note is to briefly describe a detailed (30 m) spatial dataset that estimates the degree of human modification for the lands of Colorado reflecting ~2020 conditions. The degree of human modification is a well-established method to estimate the proximate human activities or processes that have caused, are causing, or may cause impacts on biodiversity and ecosystems. This includes stressors for: urban and built-up, crop and pasture lands, livestock grazing, oil and gas production, mining and quarrying, power generation (renewable and nonrenewable), roads, railways, power lines and towers, logging and wood harvesting, human intrusions, and air pollution.

Please see the attached PDF -- Technical note on a map of human modification in Colorado for 2020 -- that provides further details.

The USDA-Agricultural Research Service carried out an experiment on water productivity in response to seasonal timing of irrigation of maize (Zea mays L.) at the Limited Irrigation Research Farm (LIRF) facility in northeastern Colorado (40°26’ N, 104°38’ W) starting in 2012. Twelve treatments involved different water availability targeted at specific growth-stages. This dataset includes data from the first two years, which were complete years with intact treatments. Data includes canopy growth and development (canopy height, canopy cover and LAI), irrigation, precipitation, and soil water storage measured periodically through the season; daily estimates of crop evapotranspiration; and seasonal measurement of crop water use, harvest index and crop yield. Hourly and daily weather data are also provided from the CoAgMET, Colorado’s network of meteorological information (https://coagmet.colostate.edu/ ; GLY04 station). Additional soil data can be found in a previous dataset (USDA-ARS Colorado Maize Water Productivity Dataset 2008-2011) also available from the Ag Data Commons. This previous dataset included six targeted treatments that were generally uniform through the season. This new dataset can be used to further validate and refine maize crop models.
The data are presented in a spreadsheet format in individual sheets within one workbook. The first sheet in the work book provides a list of data descriptions. Two sheets (one sheet for each of the two years) provide the hourly weather data, with the exception of the precipitation data, which is included in the sheet with daily data per treatment. The weather data is from a weather station on site. Another sheet provides plot level data (harvest index, yield, annual ET, maximum LAI, stand density, total aboveground biomass) taken annually by plot (four plots per treatment). Another sheet provides LAI measured four times over each season per plot. The final sheet provides daily data per treatment over each season, including data needed to compute daily water balance. This sheet has LAI, crop growth stage, plant height, estimated root depth, interpolated canopy cover, ET coefficients, precipitation, and estimated deep percolation, evaporation, and soil water deficit at four soil depths. List of files: LIRF small plots map 2012-2013 LIRF maize annual_daily_hourly data 2012-2013 Resources in this dataset:Resource Title: LIRF 2012-2013 Maize database. File Name: 2012-2013_Maize_Compiled database 06012018.xlsxResource Title: LIRF 2012-2013 Data Description. File Name: Data Description 06012018.xlsxResource Title: LIRF 2012-2013 Plot Map. File Name: Plot map 2012 2013.pdfResource Title: LIRF Data Dictionary. File Name: Data_Dictionary_Water_Prod_2012.csv

LTER - Long-Term Ecological Research Program/Kellogg Biological Station (KBS)

LTER/KBS007 (Summary adapted from the LTER Core Data Set Catalog):

Root production and turnover to depth of 1.5 m measured by minirhizotron and microvideo camera methods in alfalfa, populus, and never-tilled native succession plots of main cropping system experiment (see KBS004). Root numbers determined from video images taken at 1.2-cm intervals (2.16 cm2).

The 1,000 ha W.K. Kellogg Biological Station has been administered by Michigan State University as a primary research facility since its 1929 deeding to the university by Kellogg. In its early years the Station was devoted to wildlife, forestry, and soil conservation research; during the past 20 years a research emphasis on ecology, production agronomy, and forest genetics has led to well-established and internationally recognized programs in each of these fields. The mission of the Station, supported by 10 year-round resident faculty from several university departments, in addition to campus-based faculty and visiting scientists, puts a primary emphasis on maintaining an environment for interdisciplinary research in ecology, agriculture, and natural resources.

KBS LTER research topics include ecological interactions underlying the productivity and environmental impact of production-level cropping systems; patterns, causes, and consequences of microbial, plant, and insect diversity in agricultural landscapes; gene transfer, community dynamics and biogeochemical fluxes.

Information about LTER is also available at 'http://lternet.edu/'