Statistics illustrates market overview of maps and hydrographic or similar charts of all kinds, including atlases, wall maps, topographical plans and globes, printed in GCC from 2007 to 2024.

GCC Mobile Mapping Market is projected to grow around USD 11.8 Billion by 2031, at a CAGR of 15.8% during the forecast period.

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Section 261 of the Planning and Development Act 2000 introduced a once off system of registration for all quarries, except those for which planning permission was granted in the 5 years before Section 261 became operative

The Ground Cover Change (GGC) model's dataset is a collection of primary input and output data sources to classify regional land cover change maps. These datasets were essential to formulate a simple and automatic label supervision model to secure reliable land cover samples from multisource remote sensing data and predict accurate land cover maps, aiming to evaluate land change interactions prompted by post-disaster resettlement sites. The affected areas after the 2010 Merapi volcano eruptions in Java, Indonesia, were targeted for this research. Steps to perform data processing pipelines consist of: (1) Data collected from open-sourced datasets including the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) canopy height datasets, a land cover product, Forest Watch Canopy Heigths, and ancillary DEM-derived subsets of data. (2) These datasets were converged to perform a three-dimensional supervision of land cover samples derived from the pre-existent land cover product. (3) Highly-reliable samples were processed to redeem validation and metric sample units for multitemporal and static amplitude metric sets. (4) A filtering code was parsed with a regionally-consistent metric set to classify candidate training samples with levels of reliability based on a three-point scoring system. (5) A Random Forest model was learnt with refined training data to classify 2016-2021 Sentinel-2 satellite images over Java's tropical rainforest. (6) Land change interactions in localized areas of the Cangkringan district, Yogyakarta, Java, Indonesia, were analyzed to quantify land change interactions caused by urban resettlement sites. We found that agricultural development near resettlement sites was trending upwards despite the overall declining tendency. However, we also saw 25% forest loss, 39% built-up growth, and 43% cropland growth as a product of resettlement sites. The GCC model applies structural height vetting filters and converges statistical feature metrics to automatically detect spurious labels and classifies the data by levels of reliability. The training dataset can be nurtured annually with additional high-quality samples providing all the necessary tools (training and reference datasets) to train learning models in real-time. Given the time constraints posed by emergencies, this model becomes a valuable asset to the recovery phases of natural disasters, where our understanding of how to rebuild affected areas is limited to the traditional urban planning schemes of development. By analyzing post-disaster resettlement in the rural periphery of urban areas, resilient communities can be built with the objective of strengthening rural environments and diminishing the overall human footprint on Earth.

IRENA Copyright Info: Material in this publication may be freely used, shared, copied, reproduced, printed and/or stored, provided that all such material is clearly attributed to IRENA and bears a notation that it is subject to copyright (© IRENA 2016). Material contained in this publication attributed to third parties may be subject to third-party copy-right and separate terms of use and restrictions, including restrictions in relation to any commercial use.List of renewable energy projects in GCC as reported by Renewable Energy Market Analysis: GCC 2019

Galway County Council Planning Applications registered between 1995 and 2015. Referenced as point locations.Galway County Council provides this information with the understanding that it is not guaranteed to be accurate, correct, or complete. Galway County Council accepts no liability for any loss or damage suffered by those using this data for any purpose.

The data provided are individual thalamic GCC maps. The code was used for calculating GCC. Specifically, We calculated pair-wise Pearson correlations between the thalamocortical connectivity values of each thalamic voxel (400 functional connectivity values) and the 400 cortical gradient values. This computation generated a topographical map illustrating the correlation coefficients between the thalamocortical connectivity and the primary cortical gradient. The correlation coefficients, with Fisher's Z transformation applied, were collectively termed the gradient correlation coefficient (GCC). In sum, this method quantified the covariation between the functional connectivity profiles of each voxel in the thalamus and the cortical gradients.

Analysis of the GCC monoammonium phosphate (MAP) market from 2024-2035, featuring consumption, production, trade, and price trends for Saudi Arabia, UAE, Oman, and Kuwait, with forecasts for volume and value growth.

Green Spaces is a geospatial dataset of polygons that is a point-in-time generalized representation of existing parks and open spaces within the City of Toronto. Green Spaces includes public parks, beaches, parts of ravines, golf courses, cemeteries, and other open space areas such as those offered by various private institutions. These spaces may or may not be publicly accessible and are either publicly owned/maintained or they are privately owned/maintained. Green Spaces is not an exhaustive dataset of all the public and private parks and open spaces within the City. It does not encompass all areas protected by the Ravine and Natural Feature Protection By-Law, by Environmentally Significant Areas or by Natural Heritage Areas. Green Spaces is primarily intended to visualize our existing overall parks and open space system. It is used to symbolize the green coloured areas in many of the City's mapping products such as Toronto's Interactive Map or the Toronto Parkland Strategy[^1]. This dataset is jointly maintained by the Geospatial Competency Centre (GCC) and the Parks, Forestry & Recreation division (PFR). The attribute field in this dataset titled "AREA_CLASS" indicates whether the GCC or PFR maintain the data and the type of green space it is. PFR Green Spaces PFR Green Spaces are owned and/or operated by the City of Toronto and are derived from PFR's Parkland Asset Repository. They include the area classes: Park, Golf Course, Cemetery, Hydro Field/Utility Corridor, and others. Representation of Green Spaces can change overtime – due to new park acquisitions, development/reconfiguration of land etc. – PFR works to continuously improve the City-PFR-owned portions of this dataset as new information arises. GCC Green Spaces All other Green Spaces were created by the GCC and include area classes with the prefix of "OTHER_". These green spaces are derived through city-wide parcel analysis. [^1]This Green Spaces layer cannot be used to reproduce the results of the 2019 Parkland Strategy, however the GCC Green Spaces portions of the dataset was used to help visualize Other Open Spaces in "Figure 06: Toronto’s Parks and Open Space Network" of the report. The Toronto Parkland Strategy is currently in the process of being updated and new parkland data is not yet finalized.

Linguistic and biblical resource data for Mali

Polymer-Coated MAP Market Outlook

According to our latest research, the Global Polymer-Coated MAP market size was valued at $1.2 billion in 2024 and is projected to reach $2.8 billion by 2033, expanding at a CAGR of 9.7% during 2024–2033. The primary driver behind this robust growth is the escalating demand for enhanced efficiency fertilizers, particularly in regions facing stringent environmental regulations and a pressing need for higher agricultural productivity. Polymer-coated monoammonium phosphate (MAP) fertilizers are increasingly recognized for their ability to provide controlled nutrient release, minimize nutrient loss, and improve crop yields, making them highly attractive to both large-scale and smallholder farmers worldwide. The convergence of sustainable agriculture initiatives, rising population pressures, and innovations in fertilizer technology is expected to further accelerate the adoption of polymer-coated MAP products over the forecast period.

Regional Outlook

North America currently commands the largest share of the global Polymer-Coated MAP market, accounting for nearly 35% of the total market value in 2024. This dominance is underpinned by a mature and highly mechanized agricultural sector, widespread adoption of advanced fertilizer technologies, and robust regulatory frameworks promoting sustainable farming practices. The United States, in particular, has witnessed significant investments in precision agriculture and nutrient management solutions, driving the uptake of polymer-coated fertilizers. Additionally, the presence of leading market players, strong distribution networks, and continuous research and development activities have further solidified North America's leadership position. The region’s well-established infrastructure and supportive government policies for sustainable agriculture are expected to sustain its high market share throughout the forecast period.

In contrast, the Asia Pacific region is projected to be the fastest-growing market for polymer-coated MAP, with a remarkable CAGR of 12.3% from 2024 to 2033. This rapid expansion is fueled by burgeoning population growth, increasing food security concerns, and the intensification of agricultural activities across countries such as China, India, and Southeast Asian nations. Governments in the region are actively promoting the use of controlled-release fertilizers to address soil degradation and environmental pollution, while local manufacturers are ramping up production capacities to meet rising demand. Additionally, the region is witnessing a surge in investments from both public and private sectors aimed at modernizing agriculture and enhancing crop yields through innovative fertilizer solutions. These factors collectively position Asia Pacific as a pivotal growth engine for the global polymer-coated MAP market.

Emerging economies in Latin America and the Middle East & Africa are also experiencing a gradual increase in the adoption of polymer-coated MAP fertilizers, albeit at a slower pace compared to developed markets. In these regions, challenges such as limited farmer awareness, fragmented supply chains, and financial constraints have historically hindered widespread adoption. However, ongoing policy reforms, targeted subsidy programs, and international collaborations are beginning to address these barriers. Localized demand for high-efficiency fertilizers is being driven by the need to improve crop productivity and adapt to changing climatic conditions, particularly in Brazil, South Africa, and select Gulf Cooperation Council (GCC) countries. Over the next decade, these markets are expected to offer significant untapped potential, provided that infrastructural and educational challenges are effectively addressed.

Report Scope

The Mobile Mapping Market size was valued at USD 31.78 Billion in 2023 and is projected to reach USD 92.01 Billion by 2032, exhibiting a CAGR of 16.4 % during the forecasts period. Recent developments include: January 2023: SSP Group PLC inaugurated the casual dining concept, Lumee, at the Bahrain International Airport.December 2022: SSP Group and Bahrain Airport Company ventured together to launch the latest Lumee restaurant at the Bahrain International Airport.August 2022: Americana Restaurants International PLC declared that it made a franchise agreement with a United States-based craft coffee company, Peet's Coffee, to enter the GCC market..

The map is to be used to view the location of underground as constructed assets on the Gold Coast. This information is provided to assist in field investigations. Spot checks have been made to determine the accuracy of this plan. However, all locations, dimensions and depths shown are to be confirmed on site. Disclaimer: © Council of the City of Gold Coast, Queensland or © State of Queensland. No Warranty given in relation to the data (including accuracy, reliability, completeness or suitability) and no liability accepted (including without limitation, liability in negligence) for any loss, damage or costs (including consequential damage) relating to any use of the data. Data must not be used for direct marketing or be used in breach of the privacy laws.