The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011 and 2016. U.S. EPA leads the accuracy assessment of NLCD land cover products in coordination with USGS and SUNY-ESF. The posted dataset includes map labels and reference labels for 4629 sample locations (pixels) from the NLCD 2016 database. The sample pixels were selected using a stratified random design based on the dual 2011 – 2016 map labels. The data can be used to re-create the accuracy results reported in a forthcoming paper and in support of other applications. Accuracy results are reported for the 2011 and 2016 land cover products in the NLCD2016 database and for selected 2011-2006 changes.

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011 and 2016. U.S. EPA leads the accuracy assessment of NLCD land cover products in coordination with USGS and SUNY-ESF. The posted dataset includes map labels and reference labels for 4629 sample locations (pixels) from the NLCD 2016 database. The sample pixels were selected using a stratified random design based on the dual 2011 – 2016 map labels. The data can be used to re-create the accuracy results reported in a forthcoming paper and in support of other applications. Accuracy results are reported for the 2011 and 2016 land cover products in the NLCD2016 database and for selected 2011-2006 changes.

Across the country, public land managers make hundreds of decisions each year that influence landscapes and ecosystems within the lands they manage. Many of these decisions involve vegetation manipulations known as land treatments. Land treatments include activities such as removal or alteration of plant biomass, seeding burned areas, and herbicide applications. Data on these land treatments historically have been stored at local offices and gathering information across large spatial areas was difficult. These valuable data needed to be centralized and stored for Federal agencies involved in land treatments because these data are useful to land managers for policy and management and to scientists for developing sampling designs and studies. In 2008, the Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey (USGS) to catalog information about land treatments on federal lands in the western United States. The flexible framework of the library allows for the storage of a wide variety of data in different formats. The library contains data in text, tabular, spatial, and image formats. Specific examples include project plans and implementation reports, monitoring data, spatial data files from geographic information systems, digitized paper maps, and digital images of land treatments. The data are entered by USGS employees and are accessible through a searchable website. The LTDL can be used to respond to information requests, conduct analyses and other forms of information syntheses, produce maps, and generate reports for federal managers, scientists, and other authorized users. This data release includes the most up to date data available in the LTDL at the time of release. However, most field offices were last visited to collect their comprehensive treatment data between 2011-2014. Users should be aware that while treatments may exist in some field offices past the date of last collection, it is not a comprehensive representation of land treatments that have occurred on BLM lands during the most recent time span. Offices in southern Idaho and eastern Oregon were revisited in the winter of 2019 and the data collected during those visits are available in this release. Offices in northern Nevada were visited in 2023 and the data collected during those visits are available in this release. Several offices in southern Nevada, Utah, and Wyoming were visited in 2024, and some of the data collected during those visits are available in this release. All available post wildfire emergency stabilization and rehabilitation treatments are included for fires up to 2023.

Across the country, public land managers make hundreds of decisions each year that influence landscapes and ecosystems within the lands they manage. Many of these decisions involve vegetation manipulations known as land treatments. Land treatments include activities such as removal or alteration of plant biomass, seeding burned areas, and herbicide applications. Data on these land treatments historically have been stored at local offices and gathering information across large spatial areas was difficult. These valuable data needed to be centralized and stored for Federal agencies involved in land treatments because these data are useful to land managers for policy and management and to scientists for developing sampling designs and studies. In 2008, the Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey (USGS) to catalog information about land treatments on federal lands in the western United States. The flexible framework of the library allows for the storage of a wide variety of data in different formats. The library contains data in text, tabular, spatial, and image formats. Specific examples include project plans and implementation reports, monitoring data, spatial data files from geographic information systems, digitized paper maps, and digital images of land treatments. The data are entered by USGS employees and are accessible through a searchable website. The LTDL can be used to respond to information requests, conduct analyses and other forms of information syntheses, produce maps, and generate reports for federal managers, scientists, and other authorized users. This data release includes the most up to date data available in the LTDL at the time of release. However, most field offices were last visited to collect their comprehensive treatment data between 2011-2014. Users should be aware that while treatments may exist in some field offices past the date of last collection, it is not a comprehensive representation of land treatments that have occurred on BLM lands during the most recent time span. Offices in southern Idaho and eastern Oregon were revisited in the winter of 2019 and the data collected during those visits are available in this release. Offices in northern Nevada were visited in 2023 and the data collected during those visits are available in this release. Several offices in southern Nevada, Utah, and Wyoming were visited in 2024, and some of the data collected during those visits are available in this release. All available post wildfire emergency stabilization and rehabilitation treatments are included for fires up to 2023.

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping. Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping. Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.

장기생태연구 분야 중 육상생태계(산불지역 강우유출) 대상으로 기후변화, 환경오염 및 서식지 변화 조사 및 연구한 정보입니다.다운로드시 제공되는 스키마는 *.zip 파일과 *.csv 파일에 동일하게 적용됩니다. - 데이터 사용법 -* shape viewer 혹은 QGIS 와 같은 오픈소스 소프트웨어를 활용, shp 파일을 로딩하여 데이터를 확인할 수 있습니다. * 검색을 통하여 대한민국 지도 관련 shp를 다운받아 함께 로딩하시면 더욱 의미있는 정보를 확인하실 수 있으니 참고하시기 바랍니다. - 데이터 확장자 설명 -1. 핵심파일 *.shp: 점, 선, 또는 면으로 구현된 공간정보를 담고 있음. *.shx: shp 파일이 담고 있는 공간정보의 인덱스를 포함. *.qix: QGIS 가 이용하는 공간 인덱스 파일. *.dbf: 각 공간정보의 속성 자료, 즉 해당 공간정보의 이름, 코드번호, 면적, 길이 등의 정보를 담고 있음. 2. 보조파일 *.prj : 좌표계 정보 포함. prj 파일이 없는 경우 별도로 좌표계를 지정해 주어야 함. *.qpj : prj 파일과 연동된 파일로서, 오픈소스인 QGIS 에서 shp 파일을 활용할 때 필요. QGIS 에서 prj 파일을 호출할 때 좌표계를 혼동하는 경우가 많은데 이를 보완함. *.cpg: 쉐이프 파일의 언어를 정의. UTF-8이나 euc-kr 등으로 변경할 경우 여기에 기록됨. 모델링분석을 통한 서식지 적합성 평가 등 환경분야 평가사업(환경영향평가 등)에 활용 가능

환경부지정 습지보호지역(2020년 기준) 공간정보입니다.다운로드시 제공되는 스키마는 *.zip 파일과 *.csv 파일에 동일하게 적용됩니다. - 데이터 사용법 -* shape viewer 혹은 QGIS 와 같은 오픈소스 소프트웨어를 활용, shp 파일을 로딩하여 데이터를 확인할 수 있습니다. * 검색을 통하여 대한민국 지도 관련 shp를 다운받아 함께 로딩하시면 더욱 의미있는 정보를 확인하실 수 있으니 참고하시기 바랍니다. - 데이터 확장자 설명 -1. 핵심파일 *.shp: 점, 선, 또는 면으로 구현된 공간정보를 담고 있음. *.shx: shp 파일이 담고 있는 공간정보의 인덱스를 포함. *.qix: QGIS 가 이용하는 공간 인덱스 파일. *.dbf: 각 공간정보의 속성 자료, 즉 해당 공간정보의 이름, 코드번호, 면적, 길이 등의 정보를 담고 있음. 2. 보조파일 *.prj : 좌표계 정보 포함. prj 파일이 없는 경우 별도로 좌표계를 지정해 주어야 함. *.qpj : prj 파일과 연동된 파일로서, 오픈소스인 QGIS 에서 shp 파일을 활용할 때 필요. QGIS 에서 prj 파일을 호출할 때 좌표계를 혼동하는 경우가 많은데 이를 보완함. *.cpg: 쉐이프 파일의 언어를 정의. UTF-8이나 euc-kr 등으로 변경할 경우 여기에 기록됨. 모델링분석을 통한 서식지 적합성 평가 등 환경분야 평가사업(환경영향평가 등)에 활용 가능

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping. Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.