The market for GIS Mapping Tools is projected to reach a value of $XX million by 2033, growing at a CAGR of XX% during the forecast period (2025-2033). The market growth is attributed to the increasing adoption of GIS mapping tools by various industries, including government, utilities, and telecom, for a wide range of applications such as geological exploration, water conservancy projects, and urban planning. The convergence of GIS with other technologies such as artificial intelligence (AI) and the Internet of Things (IoT) is further driving market growth, as these technologies enable GIS mapping tools to provide more accurate and real-time data analysis. The market is segmented by type (cloud-based, web-based), application (geological exploration, water conservancy projects, urban planning, others), and region (North America, Europe, Asia Pacific, Middle East & Africa). North America is expected to remain the largest market for GIS mapping tools throughout the forecast period, due to the early adoption of these technologies and the presence of leading vendors such as Esri, MapInfo, and Autodesk. Asia Pacific is expected to experience the highest growth rate during the forecast period, due to the increasing adoption of GIS mapping tools in emerging economies such as China and India. Key industry players include Golden Software Surfer, Geoway, QGIS, GRASS GIS, Google Earth Pro, CARTO, Maptive, Shenzhen Edraw Software, MapGIS, Oasis montaj, DIVA-GIS, Esri, MapInfo, Autodesk, BatchGeo, Cadcorp, Hexagon, Mapbox, Trimble, and ArcGIS.

Panama Vegetation Time Series Maps for 1990-2016 with preliminary 2020 deforestation data. (the official 2020/21 map will be made available at the end of the 2021 mapping period).The following components are provided: "PVCTSYYYYvN" are 30m resolution raster maps resulting from compositing of 60-100 classified Landsat images for each time step, where YYYY is the nominal year of the compositing time period. (1991 includes images from 1987-1991. 2001 includes images from 1997-2001. 2006 includes images from 2002-2006. 2011 includes images from 2007-2011. 2016 includes images from 2012-2016.) Maps are all in GeoTiff format."PVCTS_key.lyr" is a layer file that can be applied in ArcGIS for optimal display of categories."PVCTSColorKey" provides more detailed description of categories and can be used to create a key in other software. More details about the land cover classes can be found in the "PVCTSv2_SupplementaryInfo" file."PVCTSdeforest7cat_YYXX" are corresponding deforestation maps for activity occurring between years YY and XX. "Deforest7cat.lyr" provides the layer file that can be applied in ArcGIS for suggested viewing and "PVCTS_Deforestation_ColorKey" provides a description of the categories and can be used to create a key in other software."PVCTSv2_SupplementaryInfo" provides information about the methods and data in the PVCTS composite and deforestation files. Accuracy assessments and error adjustments for the current PVCTS version are included in this document."MaxAgeYYYY" are maximum-vegetation-age raster maps based on aggregation of clearing observations from all images in the USGS Landsat archive with cloud-cover

This is a raster-based suitability map of landfill sites produced after the February 6, 2023, Türkiye earthquakes centred on Kahramanmaraş - Pazarcık and Kahramanmaraş - Elbistan. In this study, a site selection model was developed using open-source Geographic Information Systems (GIS) software and the Best-Worst Method (BWM), one of the Multi-Criteria Decision-Making Methods, to determine the most suitable landfill areas immediately after the earthquake.The suitability map of the landfill sites can be accessed through the Serverless Cloud-GIS based Disaster Management Portal at https://web.itu.edu.tr/metemu/nominal/deprem.htmlThe pairwise comparison matrix, weight calculation, and sensitivity analysis are also provided in the MS Excel file.

Based on the collection of GPS and stress data of the Qinghai Tibet Plateau, this paper combs the movement rate and stress deformation system of the Qinghai Tibet Plateau, displays the direction and size of each point through MAPGIS software, and then superimposes it on several main tectonic units of Songpan Ganzi flysch belt, North Qiangtang Changdu Simao plate, South Qiangtang Baoshan block and Gangdise Lhasa block. This paper tries to reflect the similarities and differences of the specific deformation modes of each block under the overall stress of the Qinghai Tibet Plateau, and further define the specific deformation style and deformation state of each local area. This is of great significance for a deep understanding of the Cenozoic deformation model of the Qinghai Tibet Plateau, as well as for guiding local disaster prevention and relief and engineering construction.

The main contents of the map include rock (ore) core recovery rate, horizon and thickness of rock or ore body, description of rock (ore) core characteristics (including material composition, structure and structure of rock and ore, contact relationship of rock or ore layer and dip angle of bedding plane, etc.), sampling and testing, etc. After the completion of drilling construction, according to the lithologic distribution of geological logging, combined with the results of sample analysis, according to REO ≥ 1%, Mo ≥ 0.03%, the rare earth ore bed and molybdenum ore bed are re divided by comprehensive research, which is completed by using MAPGIS software. The map reflects the information of borehole lithology and mineralization in the form of graphics, which is the main basis for compiling comprehensive maps and delineating rare earth ore bodies.

The main contents of the map include rock (ore) core recovery rate, horizon and thickness of rock or ore body, description of rock (ore) core characteristics (including material composition, structure and structure of rock and ore, contact relationship of rock or ore layer and dip angle of bedding plane, etc.), sampling and testing, etc. After the completion of drilling construction, according to the lithologic distribution of geological logging, combined with the results of sample analysis, according to REO ≥ 1%, Mo ≥ 0.03%, the rare earth ore bed and molybdenum ore bed are re divided by comprehensive research, which is completed by using MAPGIS software. The map reflects the information of borehole lithology and mineralization in the form of graphics, which is the main basis for compiling comprehensive maps and delineating rare earth ore bodies.

This map is a mineralization element map of the southern mining area of Geji Town in the western section of the Gangdise Mountains on the Qinghai Tibet Plateau, drawn on a scale of 1:250000. The drawing software includes MAPGIS and CorelDRAW. This map system reveals the regional ore controlling elements and the geological background of mineralization. The map is clearly divided into lithological units through multi-color blocks, where yellow green and light green bases represent surrounding rock strata such as sandstone and granite, and red block areas are marked with mineralized bodies and ore controlling structures, visually presenting the contact relationship between veins and surrounding rock. The mineral types are mainly copper and gold mineralization points, with a small amount of iron, lead, zinc and other mineral points. The spatial distribution of mineral deposits (points) is controlled by faults and fold structures, indicating the key role of tectonic activity in mineralization. This map integrates geological, structural, and mineral information, providing important basis for regional prospecting and exploration, indicating that the southern mining area of Geji Town has significant potential for copper and gold polymetallic mineralization. Subsequent research can focus on the mechanism of structural magmatic coupling controlling mineralization. There is no elevation point or other information in the figure.