Starting with Version 14, WARM is also available as a tool based on a database developed in open life cycle assessment (openLCA) software. Users can download the current version of WARM, which matches the corresponding Excel version of WARM.
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Warning This workaround may make a computer or a network more vulnerable to attack by malicious users or by malicious software such as viruses. We do not recommend this workaround but are providing this information so that you can implement this workaround at your own discretion. Use this workaround at your own risk.Warning This article offers information about how to work around issues that are caused by changes in this release of Windows Help. However, Microsoft makes no specific recommendations about which registry keys and which values are right for your organization. Your IT department is the best judge of how to weigh the advantages of these workarounds against the risks of using them. The safer course is to use no registry workarounds at all.The WinHlp32.exe download provides Group Policy settings and registry entries to work around two known issues in this release of Windows Help. By using the following Group Policy settings or registry entries, network administrators and individual users can re-enable macros and unblock .hlp files that are stored on intranet sites. A local computer Group Policy setting and a current user Group Policy setting are provided as a workaround for each feature. You can also use a user registry setting to manage each feature.For each feature, precedence is given in the following order:
Maybe I wasn't clear. When a software update happens, it is downloading data in the form of the new software onto my computer. As you know, Mac OS updates are quite large. I have a limit of 20 gigs a month on my satellite internet data plan, so 4 or more gigs is a significant portion of my monthly data allowance. I accidentally started the download and had no way of stopping it. This is the dilemma. Still unsolved.
Thanks for your response. On the latest Catalina update, this window you screenshot disappeared, nowhere to be found. When I went to Software Update it went through the process of determining I didn't have the most recent OS, and asked again if I wanted to download and update it. But it was clearly already running because I have a data use meter that was quickly downloading the large update. I tried to stop the process in Activity Monitor, but it wouldn't stop. I shut off my computer, turned it back on, and it appeared to stop, but when I returned home later in the day it had completed the download.
The strength and emphasis of the CDL is crop-specific land cover categories. The accuracy of the CDL non-agricultural land cover classes is entirely dependent upon the USGS, National Land Cover Database (NLCD). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover.The training and validation data used to create and accuracy assess the CDL has traditionally been based on ground truth data that is buffered inward 30 meters. This was done 1) because satellite imagery (as well as the polygon reference data) in the past was not georeferenced to the same precision as now (i.e. everything "stacked" less perfectly), 2) to eliminate from training spectrally-mixed pixels at land cover boundaries, and 3) to be spatially conservative during the era when coarser 56 meter AWiFS satellite imagery was incorporated. Ultimately, all of these scenarios created "blurry" edge pixels through the seasonal time series which it was found if ignored from training in the classification helped improve the quality of CDL. However, the accuracy assessment portion of the analysis also used buffered data meaning those same edge pixels were not assessed fully with the rest of the classification. This would be inconsequential if those edge pixels were similar in nature to the rest of the scene but they are not as they tend to be more difficult to classify correctly. Thus, the accuracy assessments as have been presented are inflated somewhat.Beginning with the 2016 CDLs we published both the traditional "buffered" accuracy metrics and the new "unbuffered" accuracy assessments. The purpose of publishing both versions is to provide a benchmark for users interested in comparing the different validation methods. For the 2017 CDL season we are now only publishing the unbuffered accuracy assessments within the official metadata files and offer the full "unbuffered" error matrices for download on this FAQs webpage. We plan to continue producing these unbuffered accuracy assessments for future CDLs. However, there are no plans to create these unbuffered accuracy assessments for past years. It should be noted that accuracy assessment is challenging and the CDL group has always strived to provide robust metrics of usability to the land cover community. This admission of modestly inflated accuracy measures does not render past assessments useless. They were all done consistently so comparison across years and/or states is still valid. Yet, by now providing both scenarios for 2016 gives guidance on the bias.The full error matrices are included in the downloadable links below.
To create a pixel "count" field in the attribute table of the downloaded CDL use the "Build Raster Attribute Table" Function in ESRI ArcGIS. In ESRI ArcGIS Version 9.3 and 10 this function is located at ArcToolbox > Data Management Tools > Raster > Raster Properties > Build Raster Attribute Table. Specify the downloaded CDL tif file as the Input Raster and accept all other defaults and click OK. After it has run successfully, a new "Count" data field is added to the attribute table. Count represents a raw pixel count. To calculate acreage multiply the count by the square meters conversion factor which is dependent upon the CDL pixel size. The conversion factor for 30 meter pixels is 0.222394. The conversion factor for 56 meter pixels is 0.774922.
CropScape allows users to analyze and interact with areas less than 2,000,000 square kilometers. However, users can download the entire national CDL by year by following the instructions in this FAQ question in this FAQ question (Click Here) which could then be used to perform analysis using their own GIS or image processing software.
CropScape currently does not have the capability to create PDF maps with only one specific crop or group of crops shown. However, the user can export the actual CDL data with only a single crop or subset of crops in a Geotiff (TIF) format using the CropScape "Area of Interest Statistics" tool. That downloaded data can then be used to create a more polished PDF map using ESRI ArcGIS software. Below are the procedures:1.Select your area of interest;2.Use the "Area of Interest Statistics" tool to calculate statistics;3.Check the box of the crop type(s) you wish to display in the pop-up statistical result window;4.Click "Export the selected crop(s) for mapping";5.Click the "Download" button to download the resulting image in a Geotiff (TIF) file format;6.Load the downloaded TIF file in ArcGIS where you can then add additional data, such as boundaries and/or legends, to create your own map that can then be exported to a PDF file.
In order to conform to Geospatial Data Gateway technical specifications, any CDL data downloaded through the Geospatial Data Gateway is re-projected from Albers to the dominant Universal Transverse Mercator (UTM) zone with a spheroid and datum of WGS84. The one exception to the UTM projection is for Wisconsin. Wisconsin is projected using the Wisconsin Transverse Mercator (WTM) projection. This WTM projection is based on the 1991 adjustment to NAD83, and is called WTM83/91. Projection parameters and additional information about WTM83/91 is posted on the DNR website: WTM83/91 Parameters Projection: Transverse Mercator Scale Factor at Central Meridian: 0.9996 Longitude of Central Meridian: 90 Degrees West (-90 Degrees) Latitude of Origin: 0 Degrees False Easting: 520,000 False Northing: -4,480,000 Unit: Meter Horizontal Datum: NAD83, 1991 Adjustment (aka HPGN or HARN)
If you already have GIS capability, you should be able to work with the downloadable GeoTIFF files directly in your software. If you do not have software capable of viewing a GeoTIFF (.tif) or Erdas Imagine (.IMG) file formats then we suggest using the basic viewing and GIS functionality available on the CroplandCROS web service.
The CDL Program uses medium spatial resolution (30 meter) satellite imagery. Currently, it is too costly to use higher resolution satellites to perform crop acreage estimation over large areas. The current CDL Program uses the Landsat 8 and 9 OLI/TIRS sensor, the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2, the ISRO ResourceSat-2 LISS-3, and the ESA SENTINEL-2 A and B sensors. Imagery is downloaded daily with the objective of obtaining at least one cloud-free usable image every two weeks throughout the growing season.
Detailed accuracy assessment tables are published within the official metadata files. Generally, the large area row crops have producer accuracies ranging from mid 80% to mid 90%. The full error matrices used to create the accuracy assessment information contained within the metadata files is available for download in Question 11 and 54 of this FAQs webpage. NOTE ABOUT THE UNBUFFERED VALIDATION ACCURACY TABLES BEGINNING IN 2016: The training and validation data used to create and accuracy assess the CDL has traditionally been based on ground truth data that is buffered inward 30 meters. This was done 1) because satellite imagery (as well as the polygon reference data) in the past was not georeferenced to the same precision as now (i.e. everything "stacked" less perfectly), 2) to eliminate from training spectrally-mixed pixels at land cover boundaries, and 3) to be spatially conservative during the era when coarser 56 meter AWiFS satellite imagery was incorporated. Ultimately, all of these scenarios created "blurry" edge pixels through the seasonal time series which it was found if ignored from training in the classification helped improve the quality of CDL. However, the accuracy assessment portion of the analysis also used buffered data meaning those same edge pixels were not assessed fully with the rest of the classification. This would be inconsequential if those edge pixels were similar in nature to the rest of the scene but they are not- they tend to be more difficult to classify correctly. Thus, the accuracy assessments as have been presented are inflated somewhat. Beginning with the 2016 CDL season we are creating CDL accuracy assessments using unbuffered validation data. These "unbuffered" accuracy metrics will now reflect the accuracy of field edges which have not been represented previously. Beginning with the 2016 CDLs we published both the traditional "buffered" accuracy metrics and the new "unbuffered" accuracy assessments. The purpose of publishing both versions is to provide a benchmark for users interested in comparing the different validation methods. For the 2017 CDL season we are now only publishing the unbuffered accuracy assessments within the official metadata files and offer the full "unbuffered" error matrices for download on the FAQs webpage. We plan to continue producing these unbuffered accuracy assessments for future CDLs. However, there are no plans to create these unbuffered accuracy assessments for past years. It should be noted that accuracy assessment is challenging and the CDL group has always strived to provide robust metrics of usability to the land cover community. This admission of modestly inflated accuracy measures does not render past assessments useless. They were all done consistently so comparison across years and/or states is still valid. Yet, by now providing both scenarios for 2016 gives guidance on the bias. 2ff7e9595c
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