Water Related Land Use Statewide (2018) (Features)

Feature Classes are loaded onto tablet PCs and Field crews are sent to label the crop or land cover type and irrigation method for a subset of select fields or polygons. Each tablet PC is attached to a GPS unit for real-time tracking to continuously update the field crew’s location during the field labeling process. Digitizing is done as Geodatabase feature classes using ArcMap 10.X with NAIP or Google imagery as a background with other layers added for reference. Updates to existing field boundaries of individual agricultural fields, urban areas and more are precisely digitized. Changes in irrigation type and land use are noted during this process. Cropland Data Layer (CDL) rasters from the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) are downloaded for the appropriate year. https://nassgeodata.gmu.edu/CropScape/ Zonal Statistics geoprocessing tools are used to attribute the polygons with updated crop types from the CDL. The data is then run through several stages of comparison to historical inventories and quality checking in order to determine and produce the final attributes. 2018 marked the first year a comparison could be made using the CDL methodology. The comparison between 2017 and 2018 showed a large change in agricultural land use to other land use. It was determined this shift was due to crop land being allowed to sit fallow for a season and did not represent a shift away from agricultural land. The following code amended the data: *************************************************************************************************************************************** ####On 02/07/2020 this dataset was amended with the following R script to better reflect agricultural land changes: require(arcgisbinding) arc.check_product() ####Bring in layers LU18<-arc.open("Path to data") LU18<-arc.select(LU18) #####Amend data LU18$Landuse[LU18$Class_Name=='Fallow/Idle Cropland' & LU18$Description== 'Dry Land/Other']<-"Agricultural" LU18$CropGroup[LU18$Class_Name=='Fallow/Idle Cropland' & LU18$Description== 'Dry Land/Other']<-"Fallow/Idle" LU18$IRR_Method[LU18$Class_Name=='Fallow/Idle Cropland' & LU18$Description== 'Dry Land/Other']<-"Dry Crop" arc.write("Path to data", LU18) *************************************************************************************************************************************** LUID -Unique ID number for each polygon in the final dataset, matches object. Landuse - Land use type, similar to land cover and represents our own categories of how the land is used. CropGroup - Groupings of broader crop categories to allow easy access to or query of all orchard or grain types etc. Description - Attribute that describes/indicates the various crop types and land use types determined by the GIS process. IRR_Method - Crop Irrigation Methods. Acres - Calculated acreage of the polygon. State - Spatial intersection identifying the State where the polygons are found. County - Spatial intersection identifying the County where the polygons are found. Basin - Spatial intersection identifying the Basin where the polygons are found. Basins, or Utah Hydrologic Basins are large watersheds created by DWRe. SubArea - Spatial intersection identifying the Subarea where the polygons are found. Subareas are subdivisions of the larger hydrologic basins created by DWRe. Label_Class - Combination of Label and Class_Name fields created during processing that indicates specific cover and use types. LABEL - Old shorthand descriptive label for each crop and irrigation type or land use type. Class_Name - Zonal Statistics majority value derived from the USDA CDL Cropscape raster layer, may differ from final crop determination. OldLanduse - This is the old short code found under landuse in past datasets and is kept to maintain connectivity with historical data. LU_Group - These codes represent some in-house groupings that are useful for symbology and other summarizing. SURV_YEAR - Indicates which year/growing season the data represents. Is useful when comparing to past layers.将要素类（Feature Classes）加载至平板电脑（tablet PCs），并指派野外作业人员对选定的部分地块或多边形开展作物类型、土地覆被类型及灌溉方式的标注工作。每台平板电脑均外接GPS设备（GPS unit）以实现实时追踪，在野外标注过程中持续更新作业人员的位置信息。数字化作业采用ArcMap 10.X版本的地理数据库要素类（Geodatabase feature classes）完成，以美国农业部农业航拍计划（NAIP）影像或谷歌影像作为底图，并叠加其他参考图层。本次工作将精准数字化更新单个农田、城区等现有地块的边界，并同步记录灌溉类型与土地利用的变化情况。 下载对应年份的美国农业部（United States Department of Agriculture，USDA）国家农业统计服务局（National Agricultural Statistics Service，NASS）发布的作物耕地数据层（Cropland Data Layer，CDL）栅格数据，数据来源网址为https://nassgeodata.gmu.edu/CropScape/。使用分区统计（Zonal Statistics）地理处理工具，将CDL中更新后的作物类型属性赋予各多边形。随后，将数据与历史清查数据开展多阶段对比并进行质量检查，以确定并生成最终属性字段。 2018年是首次可采用CDL方法开展对比分析的年份。2017年与2018年的对比结果显示，农业用地向其他用地类型发生了大规模转变，经研判，该变化源于耕地被休耕一季，并非农业用地整体转出。 以下代码对数据集进行了修正： *************************************************************************************************************************************** ####2020年2月7日，通过以下R脚本（R script）对数据集进行修正，以更准确地反映农业用地变化情况： require(arcgisbinding) arc.check_product() ####导入图层 LU18<-arc.open("数据路径") LU18<-arc.select(LU18) #####修正数据 LU18$Landuse[LU18$Class_Name=='Fallow/Idle Cropland' & LU18$Description== 'Dry Land/Other']<-"Agricultural" LU18$CropGroup[LU18$Class_Name=='Fallow/Idle Cropland' & LU18$Description== 'Dry Land/Other']<-"Fallow/Idle" LU18$IRR_Method[LU18$Class_Name=='Fallow/Idle Cropland' & LU18$Description== 'Dry Land/Other']<-"Dry Crop" arc.write("数据路径", LU18) *************************************************************************************************************************************** 本次数据集包含以下属性字段： - LUID：最终数据集中每个多边形的唯一标识符，与对象ID匹配。 - Landuse：土地利用类型，与土地覆被概念相近，代表项目组自定义的土地利用分类体系。 - CropGroup：宽泛的作物类别分组，便于快速访问或查询所有果园、谷物类等作物类型。 - Description：描述各作物类型与土地利用类型的属性字段，由GIS处理流程确定。 - IRR_Method：作物灌溉方式。 - Acres：多边形对应的计算所得英亩面积。 - State：通过空间相交分析得到的多边形所在州。 - County：通过空间相交分析得到的多边形所在县。 - Basin：通过空间相交分析得到的多边形所在流域盆地，即犹他水文流域（Utah Hydrologic Basins），为DWRe划定的大型流域。 - SubArea：通过空间相交分析得到的多边形所在次级区域，即由DWRe划定的大型水文流域的子分区。 - Label_Class：处理过程中生成的标签与Class_Name字段的组合，用于指示具体的覆被与利用类型。 - LABEL：各作物、灌溉类型或土地利用类型的旧简写描述标签。 - Class_Name：从USDA CDL Cropscape栅格图层通过分区统计得到的众数值，可能与最终确定的作物类型存在差异。 - OldLanduse：旧数据集土地利用字段下的旧短代码，保留该字段以维持与历史数据的关联性。 - LU_Group：代表部分内部分组编码，可用于符号化及其他汇总分析。 - SURV_YEAR：指示数据对应的年份或生长季，便于与历史图层进行对比分析。