To see the other types of publications on this topic, follow the link: Land use – Kansas – Data processing.
Journal articles on the topic 'Land use – Kansas – Data processing'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Land use – Kansas – Data processing.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Arsenault, Kristi R., Sujay V. Kumar, James V. Geiger, Shugong Wang, Eric Kemp, David M. Mocko, Hiroko Kato Beaudoing, et al. "The Land surface Data Toolkit (LDT v7.2) – a data fusion environment for land data assimilation systems." Geoscientific Model Development 11, no. 9 (September 5, 2018): 3605–21. http://dx.doi.org/10.5194/gmd-11-3605-2018.
Full textAbstract:
Abstract. The effective applications of land surface models (LSMs) and hydrologic models pose a varied set of data input and processing needs, ranging from ensuring consistency checks to more derived data processing and analytics. This article describes the development of the Land surface Data Toolkit (LDT), which is an integrated framework designed specifically for processing input data to execute LSMs and hydrological models. LDT not only serves as a preprocessor to the NASA Land Information System (LIS), which is an integrated framework designed for multi-model LSM simulations and data assimilation (DA) integrations, but also as a land-surface-based observation and DA input processor. It offers a variety of user options and inputs to processing datasets for use within LIS and stand-alone models. The LDT design facilitates the use of common data formats and conventions. LDT is also capable of processing LSM initial conditions and meteorological boundary conditions and ensuring data quality for inputs to LSMs and DA routines. The machine learning layer in LDT facilitates the use of modern data science algorithms for developing data-driven predictive models. Through the use of an object-oriented framework design, LDT provides extensible features for the continued development of support for different types of observational datasets and data analytics algorithms to aid land surface modeling and data assimilation.
2
Wong, S. N., and M. L. R. Sarker. "Land use/land cover mapping using multi-scale texture processing of high resolution data." IOP Conference Series: Earth and Environmental Science 18 (February 25, 2014): 012185. http://dx.doi.org/10.1088/1755-1315/18/1/012185.
Full text
3
Guliyeva, S. H. "LAND COVER / LAND USE MONITORING FOR AGRICULTURE FEATURES CLASSIFICATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 61–65. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-61-2020.
Full textAbstract:
Abstract. Remote sensing applications are directed to agricultural observation and monitoring. It has been huge of scientific papers are dedicated to the research of the contribution of remote sensing for agriculture studies. There are several global challenges needed to be considered within agriculture activities. It can be embraced by the main agriculture sector facing the obstacles impacting the production and productivity of the sector. These are the following options that can be pointed out: biomass and yield estimation; vegetation vigor and drought stress monitoring; assessment of crop phenological development; crop acreage estimation and cropland mapping; and mapping of disturbances and Land Use/Land Cover changes. In this study has been undertaken the realization of satellite-based Land Use/Land Cover monitoring based on various optical satellite data. It has been used satellite images taken from satellites AZERSKY, RapidEye, Sentinel-2B and further processed for Land Use/Land Cover classification. Following the complex approach of the supervised and unsupervised classification, the methodology has been used for satellite image processing. As the main satellite imagery for monitoring crop condition were AZERSKY taken during the growing season, from May to June of 2019 year. The study area was some part of the Sheki region, which covers the central part of the southern slope of the Greater Caucasus Mountain Range within Azerbaijan Republic. In this research work satellite imagery processing and mapping has been carried out on the basis of software application of ArcGIS Pro 2.5.
4
Seo, Bumsuk, Christina Bogner, Thomas Koellner, and Bjorn Reineking. "Mapping Fractional Land Use and Land Cover in a Monsoon Region: The Effects of Data Processing Options." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9, no. 9 (September 2016): 3941–56. http://dx.doi.org/10.1109/jstars.2016.2544802.
Full text
5
Shelestov, Andrii, and Bohdan Yailymov. "The state of actual land use monitoring in the leading countries with use of satellite data." Ukrainian journal of remote sensing, no. 12 (May 11, 2017): 59–66. http://dx.doi.org/10.36023/ujrs.2017.12.93.
Full textAbstract:
This paper provides the results of the analysis of satellite data usage for monitoring the use of agricultural land in different countries. Satellite data availability, generic data processing and retrieval approaches were analyzed from practical point of view.
6
Ferretti, A., D. Colombo, A. Fumagalli, F. Novali, and A. Rucci. "InSAR data for monitoring land subsidence: time to think big." Proceedings of the International Association of Hydrological Sciences 372 (November 12, 2015): 331–34. http://dx.doi.org/10.5194/piahs-372-331-2015.
Full textAbstract:
Abstract. Satellite interferometric synthetic aperture radar (InSAR) data have proven effective and valuable in the analysis of urban subsidence phenomena based on multi-temporal radar images. Results obtained by processing data acquired by different radar sensors, have shown the potential of InSAR and highlighted the key points for an operational use of this technology, namely: (1) regular acquisition over large areas of interferometric data stacks; (2) use of advanced processing algorithms, capable of estimating and removing atmospheric disturbances; (3) access to significant processing power for a regular update of the information over large areas. In this paper, we show how the operational potential of InSAR has been realized thanks to the recent advances in InSAR processing algorithms, the advent of cloud computing and the launch of new satellite platforms, specifically designed for InSAR analyses (e.g. Sentinel-1a operated by the ESA and ALOS2 operated by JAXA). The processing of thousands of SAR scenes to cover an entire nation has been performed successfully in Italy in a project financed by the Italian Ministry of the Environment. The challenge for the future is to pass from the historical analysis of SAR scenes already acquired in digital archives to a near real-time monitoring program where up to date deformation data are routinely provided to final users and decision makers.
7
Mainuri, Zachary Gichuru, John M. Mironga, and Samuel M. Mwonga. "Land Use/Land Cover Changes in a Disturbed River Watershed Kenya." European Journal of Engineering and Formal Sciences 3, no. 2 (August 31, 2019): 29. http://dx.doi.org/10.26417/ejef.v3i2.p29-36.
Full textAbstract:
Drivers of land use change were captured by the use of DPSIR model where Drivers (D) represented human needs, Pressures (P), human activities, State (S), the ecosystem, Impact (I) services from the ecosystem and Response (R), the decisions taken by land users. Land sat MSS and Land sat ETM+ (path 185, row 31) were used in this study. The Land sat ETM+ image (June 1987, May, 2000 and July, 2014) was downloaded from USGS Earth Resources Observation Systems data website. Remote sensing image processing was performed by using ERDAS Imagine 9.1. Two land use/land cover (LULC) classes were established as forest and shrub land. Severe land cover changes was found to have occurred from 1987-2000, where shrub land reduced by -19%, and forestry reduced by -72%. In 2000 – 2014 shrub land reduced by-45%, and forestry reduced by -64%. Forestry and shrub land were found to be consistently reducing.
8
Cehla, Béla, Ferenc Ede Búzás, Sándor Kiss, István Szűcs, and László Posta. "Possibilities of mass valuation in land use in Hungary." Acta Agraria Debreceniensis, no. 1 (June 1, 2021): 59–68. http://dx.doi.org/10.34101/actaagrar/1/9218.
Full textAbstract:
Technological development makes it possible to simplify and accelerate decision-making processes by adequately processing and evaluating large volumes of data. Sub-data obtained from large data sets have a very important practical role in asset valuation, forecasting and valuing delineated or difficult-to-map areas, or in the context of portfolio management. Land valuation is a separate segment within asset valuation and it requires a specific methodological approach on behalf of evaluators. In this study, the authors compared the transaction data of arable land and the value of other land use categories. Based on empirical assessments, the authors developed proposals for the fast and cost-effective determination of the value of land use categories other than arable land - mainly meadows and pastures.
9
Malandra, Francesco, Alessandro Vitali, Carlo Urbinati, and Matteo Garbarino. "70 Years of Land Use/Land Cover Changes in the Apennines (Italy): A Meta-Analysis." Forests 9, no. 9 (September 8, 2018): 551. http://dx.doi.org/10.3390/f9090551.
Full textAbstract:
Land use science usually adopts a case study approach to investigate landscape change processes, so we considered a meta-analysis an appropriate tool for summarizing general patterns and heterogeneous findings across multiple case studies over a large geographic area. Mountain landscapes in the Apennines (Italy) have undergone significant variations in the last century due to regional and national socio-economic changes. In this work, we reviewed 51 manuscripts from different databases and examined 57 case studies. We explored heterogeneous data sets, adopting a stepwise approach to select the case studies: Step 1, a general overview of the main studies; Step 2, an analysis of the features of the study sites and of land-use/cover transitions; Step 3, a landscape pattern analysis. We standardized the processing methods to obtain a new set of homogeneous data suitable for comparative analysis. After some pre-processing of the selected paper due to the broad heterogeneity of the data, we calculated common landscape metrics ex novo. We obtained digital images used to perform automatic segmentation with eCognition Developer 64 software. Our review indicated that most case studies were in Central and Southern Italy, 83% were examined at local scale, 77% carried out change detection, but only 38% included both change detection and landscape spatial pattern analysis. The results revealed a clear trend of forest expansion (+78%) and the reduction of croplands (−49%) and grasslands (−19%). We did not find significant changes in the landscape spatial patterns.
10
Nivedita Priyadarshini, K., M. Kumar, S. A. Rahaman, and S. Nitheshnirmal. "A COMPARATIVE STUDY OF ADVANCED LAND USE/LAND COVER CLASSIFICATION ALGORITHMS USING SENTINEL-2 DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5 (November 19, 2018): 665–70. http://dx.doi.org/10.5194/isprs-archives-xlii-5-665-2018.
Full textAbstract:
<p><strong>Abstract.</strong> Land Use/ Land Cover (LU/LC) is a major driving phenomenon of distributed ecosystems and its functioning. Interpretation of remote sensor data acquired from satellites requires enhancement through classification in order to attain better results. Classification of satellite products provides detailed information about the existing landscape that can also be analyzed on temporal basis. Image processing techniques acts as a platform for analysis of raw data using supervised and unsupervised classification algorithms. Classification comprises two broad ranges in which, the analyst specifies the classes by defining the training sites called supervised classification where as automatically clustering of pixels to the defined number of classes namely the unsupervised classification. This study attempts to perform the LU/LC classification for Paonta Sahib region of Himachal Pradesh which is a major industrial belt. The data obtained from Sentinel 2A, from which the stacked bands of 10<span class="thinspace"></span>m resolution are only used. Various classification algorithms such as Minimum Distance, Maximum Likelihood, Parallelepiped and Support Vector Machine (SVM) of supervised classifiers and ISO Data, K-Means of unsupervised classifiers are applied. Using the applied classification results, accuracy assessment is estimated and compared. Of these applied methods, the classification method, maximum likelihood provides highest accuracy and is considered to be the best for LU/LC classification using Sentinel-2A data.</p>
11
Borja, M. O., R. Camargo, N. Moreno, E. Turpo, and S. Villacis. "A LONG-TERM LAND COVER AND LAND USE MAPPING METHODOLOGY FOR THE ANDEAN AMAZON." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W12-2020 (November 6, 2020): 373–78. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w12-2020-373-2020.
Full textAbstract:
Abstract. The data developed by the MapBiomas Amazon initiative ( http://amazonia.mapbiomas.org/ ) led by the Amazon Geo-referenced Socio-environmental Information Network’s (RAISG) is of unprecedented spatial and temporal resolution for the Andes region. It’s comprised by a series of annual maps for the years 2000 to 2017 that allow to monitor the extent of transformation in this region using a single regional methodological approach. Several variables were included to solve Andes-specific methodological challenges and they represent adaptations of RAISG’s Amazonian methodology to the Andean region. Among such, is the use of the novel NDFIb index (Turpo, 2018), an adaptation of the NDFI index that aims at mapping Andean Wetlands. Glaciers identification was aided by the fractional abundance of snow (Turpo, 2018), as well as small water bodies identification with McFeeters (1996) NDWI water index. This experience unfolds promising accessibility to novel land cover and land use regional reconstructions and comparisons possible only by the use of large-scale cloud-computing data processing tools, open source technology, spatially and temporally comprehensive remote sensing data, along with RAISG’s standardized protocols and frameworks.
12
Seo, B., C. Bogner, P. Poppenborg, E. Martin, M. Hoffmeister, M. Jun, T. Koellner, B. Reineking, C. L. Shope, and J. Tenhunen. "Deriving a per-field land use and land cover map in an agricultural mosaic catchment." Earth System Science Data 6, no. 2 (September 30, 2014): 339–52. http://dx.doi.org/10.5194/essd-6-339-2014.
Full textAbstract:
Abstract. Detailed data on land use and land cover constitute important information for Earth system models, environmental monitoring and ecosystem services research. Global land cover products are evolving rapidly; however, there is still a lack of information particularly for heterogeneous agricultural landscapes. We censused land use and land cover field by field in the agricultural mosaic catchment Haean in South Korea. We recorded the land cover types with additional information on agricultural practice. In this paper we introduce the data, their collection and the post-processing protocol. Furthermore, because it is important to quantitatively evaluate available land use and land cover products, we compared our data with the MODIS Land Cover Type product (MCD12Q1). During the studied period, a large portion of dry fields was converted to perennial crops. Compared to our data, the forested area was underrepresented and the agricultural area overrepresented in MCD12Q1. In addition, linear landscape elements such as waterbodies were missing in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research. The data are available at the public repository Pangaea (doi:110.1594/PANGAEA.823677).
13
Hashim, Haslina, Zulkiflee Abd Latif, and Nor Aizam Adnan. "Land use land cover analysis with pixel-based classification approach." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 3 (December 1, 2019): 1327. http://dx.doi.org/10.11591/ijeecs.v16.i3.pp1327-1333.
Full textAbstract:
<p>Rapid development in certain urban area will affect its natural features. Therefore, it is important to identify and determine the changes occur for further analysis and future development planning. This process will influence several factors such as area development, environmental issues and human social activities. The selection of remote sensing data and method will derive the accurate land use land cover maps. This research study accessed the classification accuracy of different classifier approach for land use land cover classification in urban area. The objective of this paper is to compare the accuracy of the classification for each technique used. The study was conducted in a highly urbanized area in Kuala Lumpur, Malaysia. The dataset used for this study is the multi temporal LANDSAT satellite imageries for the year of 2001,2006,2011 and 2016. The pre-processing and analysis of the dataset has been done using software ENVI 5.3. Five land use classes (Urban/built up area, Forest, Agriculture, Water Body and fallow land) were identify for classification process. The classification approach for this study is the supervised classification with two algorithms namely Maximum Likelihood (ML) and Support Vector Machine (SVM). The overall accuracy and kappa statistic of the classification indicate that support vector machine algorithm was more accurate than maximum likelihood algorithm for five different time intervals.Therefore, this classification approach is acceptable and highly recommended for mapping the changes of land cover.</p>
14
Bentley, Andrew. "Practical use of aggregator data quality metrics in a collection scenario." Biodiversity Information Science and Standards 2 (June 13, 2018): e25970. http://dx.doi.org/10.3897/biss.2.25970.
Full textAbstract:
The recent incorporation of standardized data quality metrics into the GBIF, iDigBio, and ALA portal infrastructures enables data providers with useful information they can use to clean or augment Darwin Core data at the source based on these recommendations. Numerous taxonomic and geographic based metrics provide useful information on the quality of various Darwin Core fields in this realm, while also providing input on Darwin Core compliance for others. As a provider/data manager for the Biodiversity Institute, University of Kansas, and having spent some time evaluating their efficacy and reliability, this presentation will highlight some of the positive and negative aspects of my experience with specific examples while highlighting concerns regarding the user experience and standardization of these metrics across the aggregator landscape. These metrics have indicated both data and publishing issues that have increased the utility and cleanliness of our data while also highlighting batch processing challenges and issues with the process of inferring "bad" data. The integration of these metrics into source database infrastructure will also be postulated, with Specify Software as an example.
15
Seo, B., C. Bogner, P. Poppenborg, E. Martin, M. Hoffmeister, M. Jun, T. Koellner, B. Reineking, C. L. Shope, and J. Tenhunen. "Deriving a per-field land use and land cover map in an agricultural mosaic catchment." Earth System Science Data Discussions 7, no. 1 (April 30, 2014): 271–304. http://dx.doi.org/10.5194/essdd-7-271-2014.
Full textAbstract:
Abstract. Detailed data on land use and land cover constitutes important information for Earth system models, environmental monitoring and ecosystem services research. Global land cover products are evolving rapidly, however, there is still a lack of information particularly for heterogeneous agricultural landscapes. We censused land use and land cover field by field in an agricultural mosaic catchment Haean, South Korea. We recorded the land cover types with additional information on agricultural practice and make this data available at the public repository Pangaea (doi:10.1594/PANGAEA.823677). In this paper we introduce the data, its collection and the post-processing protocol. During the studied period, a large portion of dry fields was converted to perennial crops. A comparison between our dataset and MODIS Land Cover Type (MCD12Q1) suggested that the MODIS product was restricted in this area since it does not distinguish irrigated fields from general croplands. In addition, linear landscape elements such as water bodies were not detected in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research.
16
Cordery, Simon. "An effective data processing workflow for broadband single-sensor single-source land seismic data." Leading Edge 39, no. 6 (June 2020): 401–10. http://dx.doi.org/10.1190/tle39060401.1.
Full textAbstract:
Examples of raw and processed broadband single-sensor single-source land seismic data acquired in the Middle East region have been found to be significantly noisy, and very low-frequency signal has been either missing or unrecoverable. In response, an effective and pragmatic processing workflow has been developed that substantially improves the quality of the final processed data, to the extent where we can say that original survey objectives can be met. The new workflow includes early deterministic deconvolution for a number of filtering effects in the recorded signal wavelet, with the aim of flattening the signal wavelet amplitude spectrum over the vibroseis sweep frequencies and zeroing the wavelet phase. This includes the key innovative step of converting the recorded particle motion to that of the vibroseis far-field signal, those respectively being particle acceleration and particle displacement. This significantly boosts low-frequency amplitudes relative to higher frequencies such that it becomes possible to deterministically compensate for earth's absorption using a large gain limit with less concern for overamplifying high-frequency noise. An application of a source designature compensates for the nonflat design of the pilot sweep, further increasing signal amplitudes over the low-frequency ramp-up portion of the sweep. With the flattened signal spectrum, it is possible to better assess trace noise characteristics across the full bandwidth and perform better QC for its removal. Subsequent statistical deconvolution becomes more of a correction for residual effects on the signal wavelet, and the use of trace supergrouping further mitigates the effect of noise on statistical deconvolution and other data-adaptive processes.
17
Hung, Wei-Chia, Yi-An Chen, and Cheinway Hwang. "IoT technology and big data processing for monitoring and analysing land subsidence in Central Taiwan." Proceedings of the International Association of Hydrological Sciences 382 (April 22, 2020): 103–9. http://dx.doi.org/10.5194/piahs-382-103-2020.
Full textAbstract:
Abstract. Over 1992–2018, groundwater overexploitation had caused large-scale land subsidence in the Choshui River Alluvial Fan (CRAF) in Taiwan. The Taiwan High Speed Railway (THSR) passes through an area of severe subsidence in CRAF, and the subsidence poses a serious threat to its operation. How to effectively monitor land subsidence here has become a major issue in Taiwan. In this paper, we introduce a multiple-sensor monitoring system for land subsidence, including 50 continuous operation reference stations (CORS), multi temporal InSAR (MT-InSAR), a 1000 km levelling network, 34 multi-layer compaction monitoring wells and 116 groundwater monitoring wells. This system can monitor the extent of land subsidence and provide data for studying the mechanism of land subsidence. We use the Internet of Things (IoT) technology to control and manage the sensors and develop a bigdata processing procedure to analyse the monitoring data for the system of sensors. The procedure makes the land subsidence monitoring more efficient and intelligent.
18
Espinoza Molina, D., K. Alonso, and M. Datcu. "SEMANTIC INDEXING OF TERRASAR-X AND IN SITU DATA FOR URBAN ANALYTICS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (December 11, 2015): 185–88. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-185-2015.
Full textAbstract:
This paper presents the semantic indexing of TerraSAR-X images and in situ data. Image processing together with machine learning methods, relevance feedback techniques, and human expertise are used to annotate the image content into a land use land cover catalogue. All the generated information is stored into a geo-database supporting the link between different types of information and the computation of queries and analytics. We used 11 TerraSAR-X scenes over Germany and LUCAS as in situ data. The semantic index is composed of about 73 land use land cover categories found in TerraSAR-X test dataset and 84 categories found in LUCAS dataset.
19
Ostadabbas, H., H. Weippert, and F. J. Behr. "DATABASE TRANSFORMATION, CADASTRE AUTOMATIC DATA PROCESSING IN QGIS AND IMPLEMENTATION IN WEB GIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W14 (August 23, 2019): 175–78. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w14-175-2019.
Full textAbstract:
<p><strong>Abstract.</strong> On the judicial basis of § 196 Baugesetzbuch (BauGB, 2018) every municipality in the Federal Republic of Germany must publish standard land values in €/m<sup>2</sup> for its whole district area in a biennial cycle. The standard land values have to be derived comprehensively for different land use categories within this district. With the help of Geographic Information Systems (GIS) all the necessary data for the derivation of the standard land values can be analyzed. This data consists of cadastral information (ALKIS) (AdV, 2008) for each municipality district like streets, buildings, land parcels, areas of application for special building law as well as geocoded data about purchasing prices within the district’s real estate transactions. The following work contributes to both requirements, the statutory determination of the standard land values answering the legal necessity and the setting up of the generated geo data in the Web according to the transparency demanded by the European INSPIRE (Infrastructure for Spatial Information in Europe) directive. This report describes the implementation of the automated process of the setup of the relevant data layers based on ALKIS data in an Open Source GIS (QGIS) using SQL and Python scripts. The standard land values are visualized and presented in a Web GIS. After the evaluation of different alternatives, QGIS Server and Lizmap, an Open Source QGIS Web Client, were used for the web based presentation and accordingly configured.</p>
20
Priyadi, Priyadi. "Analysis of Spatio Temporal Change of Land Use of Chrysanthemum Farm in Semarang Regency Using Landsat Image 8 OLI." Indonesian Journal of Computing and Modeling 1, no. 2 (October 15, 2018): 49–54. http://dx.doi.org/10.24246/j.icm.2018.v1.i2.p49-54.
Full textAbstract:
Agriculture is a business issue that has long existed and will likely continue to exist throughout the ages. Similarly, on the issue of agricultural land use chrysanthemum that needs to be developed method of analysis using technology approach and computer science. This research intends to analyze and develop effective and efficient methods of chrysanthemum land use. The satellite imagery data covering pre-processing, processing and post processing in this research is mostly done with QGIS software. Satelite image used in this research is LANDSAT 8 OLI and band used are band 6, bang 5, band 2 and band 8. Stages of working this research include image cutting in the research area of all bands and all temporal images involved in research, pansharpening using "Orfeo toolbox", image classification with "semi-automatic clasification", then completed with analysis of land use change using "molusce". The result of this research is spatio-temporal data of two images of land use chrysanthemum in April 2017 and August 2017. The result of mathematical research is a statistical table of changes of agricultural land use on two temporal of image used as research object. In addition to the two results of the analysis data, this study also describes the digital image analysis method of agricultural land use chrysanthemum which is expected to be useful for remote sensing research on other research object or extension to this research.
21
Vennithasari, Riska, and Frederik Samuel Papilaya. "Analysis of Green Land Changes to Building Land Using Geographic Information System (GIS) in Salatiga City from 2013 to 2019." Journal of Applied Geospatial Information 4, no. 2 (July 3, 2020): 350–55. http://dx.doi.org/10.30871/jagi.v4i2.2048.
Full textAbstract:
The land is a crucial element in human life as space and resource. The development of a region will not be neglected by the use of land. Data from BPS Salatiga 2013 to 2019 shows an average increase in population reaching 1.45%. Land-use changes in a region will affect the geographical conditions of the region itself. Therefore, the latest information is needed in order to anticipate continuous changes. The research was conducted in Salatiga and the time of the study starts in August 2019 until January 2020. The purpose of this research is to see and analyze the extent of each transformation of the land use and land cover changes by utilizing Landsat 8 Satellite Imagery in 2013-2019. Data processing in this study uses spatial analysis overlay technique that combined with unsupervised classification and confusion matrix method through SAGA GIS software. The results of data processing will afford new maps and land use change tables then explained descriptively. Based on the analysis that has been done, In 2013, the land use in Salatiga was dominated by green land of 3.031,29 ha which was then followed by land use for built-up land reaching 2.033,91 ha. And in 2019, land use was still dominated by green land of 2.499,03 ha which was then followed by the use of built-up land of 2.483,64 ha. The final result of the area of Salatiga in 2013 - 2019 which experiencing land change from a green land to be built up land is 755,91 hectares.
22
Leinenkugel, Patrick, Ramona Deck, Juliane Huth, Marco Ottinger, and Benjamin Mack. "The Potential of Open Geodata for Automated Large-Scale Land Use and Land Cover Classification." Remote Sensing 11, no. 19 (September 27, 2019): 2249. http://dx.doi.org/10.3390/rs11192249.
Full textAbstract:
This study examines the potential of open geodata sets and multitemporal Landsat satellite data as the basis for the automated generation of land use and land cover (LU/LC) information at large scales. In total, six openly available pan-European geodata sets, i.e., CORINE, Natura 2000, Riparian Zones, Urban Atlas, OpenStreetMap, and LUCAS in combination with about 1500 Landsat-7/8 scenes were used to generate land use and land cover information for three large-scale focus regions in Europe using the TimeTools processing framework. This fully automated preprocessing chain integrates data acquisition, radiometric, atmospheric and topographic correction, spectral–temporal feature extraction, as well as supervised classification based on a random forest classifier. In addition to the evaluation of the six different geodata sets and their combinations for automated training data generation, aspects such as spatial sampling strategies, inter and intraclass homogeneity of training data, as well as the effects of additional features, such as topography and texture metrics are evaluated. In particular, the CORINE data set showed, with up to 70% overall accuracy, high potential as a source for deriving dominant LU/LC information with minimal manual effort. The intraclass homogeneity within the training data set was of central relevance for improving the quality of the results. The high potential of the proposed approach was corroborated through a comparison with two similar LU/LC data sets, i.e., GlobeLand30 and the Copernicus High Resolution Layers. While similar accuracy levels could be observed for the latter, for the former, accuracy was considerable lower by about 12–24%.
23
Thompson, M. W., J. Hiestermann, and L. Moyo. "PROVING THE CAPABILITY FOR LARGE SCALE REGIONAL LAND-COVER DATA PRODUCTION BY SELF-FUNDED COMMERCIAL OPERATORS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W2 (November 16, 2017): 209–12. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w2-209-2017.
Full textAbstract:
For service providers developing commercial value-added data content based on remote sensing technologies, the focus is to typically create commercially appropriate geospatial information which has downstream business value. The primary aim being to link locational intelligence with business intelligence in order to better make informed decisions. From a geospatial perspective this locational information must be relevant, informative, and most importantly current; with the ability to maintain the information timeously into the future for change detection purposes. Aligned with this, GeoTerraImage has successfully embarked on the production of land-cover/land-use content over southern Africa. The ability for a private company to successfully implement and complete such an exercise has been the capability to leverage the combined advantages of cutting edge data processing technologies and methodologies, with emphasis on processing repeatability and speed, and the use of a wide range of readily available imagery. These production workflows utilise a wide range of integrated procedures including machine learning algorithms, innovative use of non-specialists for sourcing of reference data, and conventional pixel and object-based image classification routines, and experienced/expert landscape interpretation. This multi-faceted approach to data produce development demonstrates the capability for SMME level commercial entities such as GeoTerraImage to generate industry applicable large data content, in this case, wide area coverage land-cover and land-use data across the sub-continent. Within this development, the emphasis has been placed on the key land-use information, such as mining, human settlements, and agriculture, given the importance of this geo-spatial land-use information in business and socio-economic applications and decision making.
24
Potapov, Peter, Matthew C. Hansen, Indrani Kommareddy, Anil Kommareddy, Svetlana Turubanova, Amy Pickens, Bernard Adusei, Alexandra Tyukavina, and Qing Ying. "Landsat Analysis Ready Data for Global Land Cover and Land Cover Change Mapping." Remote Sensing 12, no. 3 (January 29, 2020): 426. http://dx.doi.org/10.3390/rs12030426.
Full textAbstract:
The multi-decadal Landsat data record is a unique tool for global land cover and land use change analysis. However, the large volume of the Landsat image archive and inconsistent coverage of clear-sky observations hamper land cover monitoring at large geographic extent. Here, we present a consistently processed and temporally aggregated Landsat Analysis Ready Data produced by the Global Land Analysis and Discovery team at the University of Maryland (GLAD ARD) suitable for national to global empirical land cover mapping and change detection. The GLAD ARD represent a 16-day time-series of tiled Landsat normalized surface reflectance from 1997 to present, updated annually, and designed for land cover monitoring at global to local scales. A set of tools for multi-temporal data processing and characterization using machine learning provided with GLAD ARD serves as an end-to-end solution for Landsat-based natural resource assessment and monitoring. The GLAD ARD data and tools have been implemented at the national, regional, and global extent for water, forest, and crop mapping. The GLAD ARD data and tools are available at the GLAD website for free access.
25
Picoli, M. C. A., R. Simoes, M. Chaves, L. A. Santos, A. Sanchez, A. Soares, I. D. Sanches, K. R. Ferreira, and G. R. Queiroz. "CBERS DATA CUBE: A POWERFUL TECHNOLOGY FOR MAPPING AND MONITORING BRAZILIAN BIOMES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2020 (August 3, 2020): 533–39. http://dx.doi.org/10.5194/isprs-annals-v-3-2020-533-2020.
Full textAbstract:
Abstract. Currently, the overwhelming amount of Earth Observation data demands new solutions regarding processing and storage. To reduce the amount of time spent in searching, downloading and pre-processing data, the remote Sensing community is coming to an agreement on the minimum amount of corrections satellite images must convey in order to reach the broadest range of applications. Satellite imagery meeting such criteria (which usually include atmospheric, radiometric and topographic corrections) are generically called Analysis Ready Data (ARD). Furthermore, ARD is being assembled into multidimensional data cubes, minimising preprocessing tasks and allowing scientists and users in general to focus on analysis. A particular instance of this is the Brazil Data Cube (BDC) project, which is processing remote sensing images of medium spatial resolution into ARD datasets and assembling them as multidimensional cubes of the Brazilian territory. For example, BDC users are released from performing tasks such as image co-registration , aerosol interference correction. This work presents a BDC proof of concept, by analysing a BDC data cube made with images from the fourth China-Brazil Earth Resources Satellite (CBERS-4) of one of the largest biodiversity hotspot in the world, the Cerrado biome. It also shows how to map and monitor land use and land cover using the CBERS data cube. We demonstrate that the CBERS data cube is effective in resolving land use and and land cover issues to meet local and national needs related to the landscape dynamics, including deforestation, carbon emissions, and public policies.
26
Townsend, Margaret A., Stephen A. Macko, and David P. Young. "Distribution and Sources of Nitrate-Nitrogen in Kansas Groundwater." Scientific World JOURNAL 1 (2001): 216–22. http://dx.doi.org/10.1100/tsw.2001.331.
Full textAbstract:
Kansas is primarily an agricultural state. Irrigation water and fertilizer use data show long- term increasing trends. Similarly, nitrate-N concentrations in groundwater show long-term increases and exceed the drinking-water standard of 10 mg/l in many areas. A statistical analysis of nitrate-N data collected for local and regional studies in Kansas from 1990 to 1998 (747 samples) found significant relationships between nitrate-N concentration with depth, age, and geographic location of wells. Sources of nitrate-N have been identified for 297 water samples by using nitrogen stable isotopes. Of these samples, 48% showed fertilizer sources (+2 to +8) and 34% showed either animal waste sources (+10 to +15 with nitrate-N greater than 10 mg/l) or indication that enrichment processes had occurred (+10 or above with variable nitrate-N) or both. Ultimate sources for nitrate include nonpoint sources associated with past farming and fertilization practices, and point sources such as animal feed lots, septic systems, and commercial fertilizer storage units. Detection of nitrate from various sources in aquifers of different depths in geographically varied areas of the state indicates that nonpoint and point sources currently impact and will continue to impact groundwater under current land uses.
27
Radočaj, Dorijan, Jasmina Obhođaš, Mladen Jurišić, and Mateo Gašparović. "Global Open Data Remote Sensing Satellite Missions for Land Monitoring and Conservation: A Review." Land 9, no. 11 (October 23, 2020): 402. http://dx.doi.org/10.3390/land9110402.
Full textAbstract:
The application of global open data remote sensing satellite missions in land monitoring and conservation studies is in the state of rapid growth, ensuring an observation with high spatial and spectral resolution over large areas. The purpose of this study was to provide a review of the most important global open data remote sensing satellite missions, current state-of-the-art processing methods and applications in land monitoring and conservation studies. Multispectral (Landsat, Sentinel-2, and MODIS), radar (Sentinel-1), and digital elevation model missions (SRTM, ASTER) were analyzed, as the most often used global open data satellite missions, according to the number of scientific research articles published in Web of Science database. Processing methods of these missions’ data consisting of image preprocessing, spectral indices, image classification methods, and modelling of terrain topographic parameters were analyzed and demonstrated. Possibilities of their application in land cover, land suitability, vegetation monitoring, and natural disaster management were evaluated, having high potential in broad use worldwide. Availability of free and complementary satellite missions, as well as the open-source software, ensures the basis of effective and sustainable land use management, with the prerequisite of the more extensive knowledge and expertise gathering at a global scale.
28
Dinka, Megersa Olumana, and Degefa Dhuga Chaka. "Analysis of land use/land cover change in Adei watershed, Central Highlands of Ethiopia." Journal of Water and Land Development 41, no. 1 (June 1, 2019): 146–53. http://dx.doi.org/10.2478/jwld-2019-0038.
Full textAbstract:
Abstract Land use/land cover changes (LULCC) at Adei watershed (Ethiopia) over a period of 23 years (1986–2009) has been analysed from LANDSAT imagery and ancillary data. The patterns (magnitude and direction) of LULCC were quantified and the final land use/land cover maps were produced after a supervised classification with appropriate post-processing. Image analysis results revealed that the study area has undergone substantial LULCC, primarily a shift from natural cover into managed agro-systems, which is apparently attributed to the increasing both human and livestock pressure. Over the 23 years, the aerial coverage of forest and grass lands declined by 8.5% and 4.3%, respectively. On the other hand, agricultural and shrub lands expanded by 9.1% and 3.7%, respectively. This shows that most of the previously covered by forest and grass lands are mostly shifted to the rapidly expanding farm land use classes. The findings of this study suggested that the rate of LULCC over the study period, particularly deforestation due to the expansion of farmland need to be given due attention to maintain the stability and sustainability of the ecosystem.
29
Elaji, Amnah, and Wei Ji. "Urban Runoff Simulation: How Do Land Use/Cover Change Patterning and Geospatial Data Quality Impact Model Outcome?" Water 12, no. 10 (September 28, 2020): 2715. http://dx.doi.org/10.3390/w12102715.
Full textAbstract:
With the increase in global urbanization, satellite imagery and other types of geospatial data have been extensively used in urban landscape change research, which includes environmental modeling in order to assess the change impact on urban watersheds. For urban hydrological modeling, as a focus of this study, several related research questions are raised: (1) How sensitive are runoff simulation to land use and land cover change patterning? (2) How will input data quality impact the simulation outcome? (3) How effective is integrating and synthesizing various forms of geospatial data for runoff modeling? These issues were not fully or adequately addressed in previous related studies. With the aim of answering these questions as research objectives, we conducted a spatial land use and land cover (LULC) change analysis and an urban runoff simulation in the Blue River watershed in the Kansas City metropolitan area between 2003 and 2017. In this study, approaches were developed to incorporate the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model with remote sensing, geographic information systems (GIS), and radar rainfall data. The impact of data quality on the model simulation outcome was also analyzed. The results indicate that there are no significant differences between simulated runoff responses in the two study years (2003 and 2017) due to spatial and temporal heterogeneity of urbanization processes in the region. While the metropolitan area has been experiencing remarkable urban development in the past few decades, the gain in built-up land in the study watershed during the study period is insignificant. On the other hand, the gain in vegetated land caused by forestation activities is offset by a decrease in farmland and grassland. The results show that increasing spatial data resolution does not necessarily or noticeably improve the HEC-HMS model performance or outcomes. Under these conditions, using Next Generation Weather Radar (NEXRAD) rainfall data in the simulation provides a satisfactory fit in hydrographs’ shapes, peak discharge amounts and time after calibration efforts, while they may overestimate the amount of rainfall as compared with gauge data. This study shows that the developed approach of synthesizing satellite, GIS, and radar rainfall data in hydrological modeling is effective and useful for incorporating urban landscape and precipitation change data in dynamic flood risk assessment at a watershed level.
30
Sirindhorn, H. R. H. Princess Maha Chakri, Korapin Srisuksawadi, and Siriwan Silapacharanan. "Land use/land cover map accuracy assessment of Landsat Thematic Mapper data using the DIMAPS image processing system for Narathiwat Province, Thailand." Geocarto International 5, no. 1 (March 1990): 15–24. http://dx.doi.org/10.1080/10106049009354244.
Full text
31
Lovita, Oktalia Triananda, and Resky Rusnanda. "Geographic Information System in Mapping Land Use in South Aceh District." Jurnal Inotera 3, no. 2 (December 31, 2018): 70. http://dx.doi.org/10.31572/inotera.vol3.iss2.2018.id56.
Full textAbstract:
The dawn of the age of computerization has opened up a new horizon and paradigm in the decision making process and dissemination of information. In the past difficulties arise when a large bulk of data representing of modeling a certain phenomenon was to be compiled because these data were often detached from each other. With Geographic Information System (GIS), the storing, administration, processing, manipulation, analysis and exhibition of important data in a system of information can be done with ease and speed. This study attempts to represent and model the available data of Sourt Aceh Selatan concerning its administrative boundaries, land, geology, land use and slope, Using ArcGIS 10.3, a GIS software that is capable to represent spatial data as well as attributes of the study areas. the results of rms error on landsat 8 oil images obtained mean 0.51, GIS technology in civil engineering work is normally used in the planning and preparation of a new land for the development of a housing complex.
32
Ukkola, Anna M., Ned Haughton, Martin G. De Kauwe, Gab Abramowitz, and Andy J. Pitman. "FluxnetLSM R package (v1.0): a community tool for processing FLUXNET data for use in land surface modelling." Geoscientific Model Development 10, no. 9 (September 12, 2017): 3379–90. http://dx.doi.org/10.5194/gmd-10-3379-2017.
Full textAbstract:
Abstract. Flux towers measure ecosystem-scale surface–atmosphere exchanges of energy, carbon dioxide and water vapour. The network of flux towers now encompasses ∼ 900 sites, spread across every continent. Consequently, these data have become an essential benchmarking tool for land surface models (LSMs). However, these data as released are not immediately usable for driving, evaluating and benchmarking LSMs. Flux tower data must first be transformed into a LSM-readable file format, a process which involves changing units, screening missing data and varying degrees of additional gap-filling. All of this often leads to an under-utilisation of these data in model benchmarking. To resolve some of these issues, and to help make flux tower measurements more widely used, we present a reproducible, open-source R package that transforms the FLUXNET2015 and La Thuile data releases into community standard NetCDF files that are directly usable by LSMs. We note that these data would also be useful for any other user or community seeking to independently quality control, gap-fill or use the FLUXNET data.
33
Zhang, Xiao Lun, Shu Gan, Ying Li, Ji Lei Huang, and Shuai Gao. "Remote Sensing Integration Survey of Typical Land Types and Analysis of its Spectral Properties in Southeast of Yunnan Province." Applied Mechanics and Materials 444-445 (October 2013): 1239–43. http://dx.doi.org/10.4028/www.scientific.net/amm.444-445.1239.
Full textAbstract:
Karst rocky desertification is a major ecological disaster faced by the southeastern region of Yunnan Province, in China. The research of land use status in rocky desertification area is more and more concerned by human. Through remote sensing integrated survey ways to establish the spectral database of six kinds of typical land types, such as water, forest land, paddy field, grassland, dry land and bare land; then, Normalized Difference Vegetation Index (NDVI) processing and Tasseled Cap transformation processing for the spectral data; finally, the spectral characteristics and the variation of typical land types was analyzed and studied. The results indicated that, there are no significant differences of spectral of the six kinds of typical land types, after the processing of NDVI, the water, the forest land and grassland with larger vegetation coverage, and the paddy land, dry land and bare land with smaller vegetation coverage, can be well distinguish, but the distinction between forest land and grassland is bad, the distinction of paddy land, dry land and bare land is also bad; after the Tasseled Cap transformation processing, the dispersion degree of water, forest land, paddy field and grassland is better, the dispersion degree of dry land and bare land is a bit poor, need to be further studied. The remote sensing integrated survey and the analysis of spectral properties are important foundation for the Land Use / Land Cover Change (LUCC) and the dynamic monitoring of rocky desertification in southeastern rocky desertification region of Yunnan province.
34
Yang, Jun, Weiling Liu, Yonghua Li, Xueming Li, and Quansheng Ge. "Simulating Intraurban Land Use Dynamics under Multiple Scenarios Based on Fuzzy Cellular Automata: A Case Study of Jinzhou District, Dalian." Complexity 2018 (August 27, 2018): 1–17. http://dx.doi.org/10.1155/2018/7202985.
Full textAbstract:
The spatial evolution of land use in Jinzhou area was simulated using fuzzy cellular automata to determine all factors influencing urban land use change. For this purpose, land use data of multiple sources and remote sensing images from 2003 to 2015 were analyzed. The following results were obtained: (1) real land use data and simulation data for 2015 were tested using four indices. Under the 5 m × 5 m scale, the model shows good performance for simulation of areas with various land use types. (2) Among simulations under four scenarios, the effect of traffic guidance on the development of construction land was more distinct under the economic development mode, which clearly showed the phenomenon of “agglomeration” along major traffic lines. (3) Jinshitan Street is adjacent to the sea, and land use changes are significant under the 4th scenario, and thus related departments should pay more attention. (4) Shortcomings of conventional cellular automata model in processing complex systems could be mitigated through the integration of fuzzy sets.
35
Topaloğlu, Raziye Hale, Elif Sertel, and Nebiye Musaoğlu. "ASSESSMENT OF CLASSIFICATION ACCURACIES OF SENTINEL-2 AND LANDSAT-8 DATA FOR LAND COVER / USE MAPPING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1055–59. http://dx.doi.org/10.5194/isprsarchives-xli-b8-1055-2016.
Full textAbstract:
This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.
36
Topaloğlu, Raziye Hale, Elif Sertel, and Nebiye Musaoğlu. "ASSESSMENT OF CLASSIFICATION ACCURACIES OF SENTINEL-2 AND LANDSAT-8 DATA FOR LAND COVER / USE MAPPING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1055–59. http://dx.doi.org/10.5194/isprs-archives-xli-b8-1055-2016.
Full textAbstract:
This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.
37
Fadda, Eyad H., Fatemah Al Shebli, and Ayshah Al Kabi. "The Use of Remote Sensing and GIS to Study Land Use Changes in Barka Wilaya, Oman." Journal of Arts and Social Sciences [JASS] 10, no. 1 (April 30, 2019): 15. http://dx.doi.org/10.24200/jass.vol10iss1pp15-20.
Full textAbstract:
Many studies house indicated the increase of the proportion of urban areas over the arable land in many provinces of the Sultanate of Oman. This came as a result of urban growth and development processes taking place since the era of the Renaissance which started in 1970. Consequently, spatial variation in land use is an important issue to be taken into consideration, because lands are being converted to be less productive, due to the lack of raw soil, vegetation, and water as a result of human exploitation of the limited resources in different ways, in addition to the natural factors of droughts and floods and all that will eventually lead to land degradation. Barka province (wilayat) in al Batinah Governorate is one of the provinces, which has been affected by land cover/land use changes due to several reasons. Therefore, this study will focus on the determination of land use changes, whether commercial or residential that have been occurred in the province, in addition to the loss of agricultural areas and fertile land during the period from 1987 to 2015. Remote sensing and geographic information system (GIS) were utilized in order to delineate and to determine the cause of shrinking in the arable land and fertile land. Satellite images were used to detect the change in land use/land cover by applying selective digital image processing techniques such as supervised classification and change detection. Thematic maps were prepared using GIS software with attribute data about the land uses in the study area, which highlights and show the impact of urban growth on land degradation.
38
Husein, Haifaa, Oday Jasim, and Saja Mahmood. "Proposal of building a standard geodatabase for urban land use." MATEC Web of Conferences 162 (2018): 03024. http://dx.doi.org/10.1051/matecconf/201816203024.
Full textAbstract:
The digital technologies represented by digital processing programs, local data bases and satellite receivers system is a set of technologies made to organize the process of building descriptive field database, and conveying them to computers, in order to store, analyze and manifest data as well as upgrade and extract it in the form of digital maps, which represent an asset in any engineering and planning study. For a variety of types of mixed land uses and others land uses in the urban city, which cause great difficulty in how to build spatial Geodatabase in terms of frequency of the land use and overlap between land uses, the paper will find the proposed standard Geomatics techniques to get rid of these difficulties. The paper will tackle the engineering and survey methods which could reinforce manifestation of uses of logical database in urban areas. Lastly, the research concludes that relying on important field survey and digital references in preparing suggested criteria for field uses, in addition to the recommendations provided in this field for the post graduate and undergraduate students as well governmental specialized departments.
39
Malinowski, Radek, Stanisław Lewiński, Marcin Rybicki, Ewa Gromny, Małgorzata Jenerowicz, Michał Krupiński, Artur Nowakowski, et al. "Automated Production of a Land Cover/Use Map of Europe Based on Sentinel-2 Imagery." Remote Sensing 12, no. 21 (October 27, 2020): 3523. http://dx.doi.org/10.3390/rs12213523.
Full textAbstract:
Up-to-date information about the Earth’s surface provided by land cover maps is essential for numerous environmental and land management applications. There is, therefore, a clear need for the continuous and reliable monitoring of land cover and land cover changes. The growing availability of high resolution, regularly collected remote sensing data can support the increasing number of applications that require high spatial resolution products that are frequently updated (e.g., annually). However, large-scale operational mapping requires a highly-automated data processing workflow, which is currently lacking. To address this issue, we developed a methodology for the automated classification of multi-temporal Sentinel-2 imagery. The method uses a random forest classifier and existing land cover/use databases as the source of training samples. In order to demonstrate its operability, the method was implemented on a large part of the European continent, with CORINE Land Cover and High-Resolution Layers as training datasets. A land cover/use map for the year 2017 was produced, composed of 13 classes. An accuracy assessment, based on nearly 52,000 samples, revealed high thematic overall accuracy (86.1%) on a continental scale, and average overall accuracy of 86.5% at country level. Only low-frequency classes obtained lower accuracies and we recommend that their mapping should be improved in the future. Additional modifications to the classification legend, notably the fusion of thematically and spectrally similar vegetation classes, increased overall accuracy to 89.0%, and resulted in ten, general classes. A crucial aspect of the presented approach is that it embraces all of the most important elements of Earth observation data processing, enabling accurate and detailed (10 m spatial resolution) mapping with no manual user involvement. The presented methodology demonstrates possibility for frequent and repetitive operational production of large-scale land cover maps.
40
Nugroho, Jalu Tejo, Zylshal, Nurwita Mustika Sari, and Dony Kushardono. "A COMPARISON OF OBJECT-BASED AND PIXEL-BASED APPROACHES FOR LAND USE/LAND COVER CLASSIFICATION USING LAPAN-A2 MICROSATELLITE DATA." International Journal of Remote Sensing and Earth Sciences (IJReSES) 14, no. 1 (June 21, 2017): 27. http://dx.doi.org/10.30536/j.ijreses.2017.v14.a2680.
Full textAbstract:
In recent years, small satellite industry has been a rapid trend and become important especially when associated with operational cost, technology adaptation and the missions. One mission of LAPAN-A2, the 2nd generation of microsatellite that developed by Indonesian National Institute of Aeronautics and Space (LAPAN), is Earth observation using digital camera that provides imagery with 3.5 m spatial resolution. The aim of this research is to compare between object-based and pixel-based classification of land use/land cover (LU/LC) in order to determine the appropriate classification method in LAPAN-A2 dataprocessing (case study Semarang, Central Java).The LU/LC were classified into eleven classes, as follows: sea, river, fish pond, tree, grass, road, building 1, building 2, building 3, building 4 and rice field. The accuracy of classification outputs were assessed using confusion matrix. The object-based and pixel-based classification methods result for overall accuracy are 31.63% and 61.61%, respectively. According to accuracy result, it was thought that blurring effect on LAPAN-A2 data may be the main cause ofaccuracy decrease. Furthermore, the result is suggested to use pixel-based classification to be applied inLAPAN-A2 data processing.
41
Amarsaikhan, D., V. Battsengel, E. Egshiglen, R. Gantuya, and D. Enkhjargal. "Applications of GIS and Very High-Resolution RS Data for Urban Land Use Change Studies in Mongolia." International Journal of Navigation and Observation 2011 (December 27, 2011): 1–8. http://dx.doi.org/10.1155/2011/314507.
Full textAbstract:
The aim of this study is to analyze the urban land use changes occurred in the central part of Ulaanbaatar, the capital city of Mongolia, from 1930 to 2008 with a 10-year interval using geographical information system (GIS) and very high-resolution remote sensing (RS) data sets. As data sources, a large-scale topographic map, panchromatic and multispectral Quickbird images, and TerraSAR synthetic aperture radar (SAR) data are used. The primary urban land use database is developed using the topographic map of the study area and historical data about buildings. To extract updated land use information from the RS images, Quickbird and TerraSAR images are fused. For the fusion, ordinary and special image fusion techniques are used and the results are compared. For the final land use change analysis and RS image processing, ArcGIS and Erdas imagine systems installed in a PC environment are used. Overall, the study demonstrates that within the last few decades the central part of Ulaanbaatar city is urbanized very rapidly and became very dense.
42
Sant'Anna, Aline Cristina, Mateus José Rodrigues Paranhos da Costa, Adriano Gomes Páscoa, Lívia Carolina Magalhães Silva, and Jens Jung. "Assessing land use by cattle in heterogeneous environments." Ciência Rural 45, no. 3 (March 2015): 470–73. http://dx.doi.org/10.1590/0103-8478cr20131576.
Full textAbstract:
The aim of this note is to describe preliminary results on assessment of land use by cattle, obtained in a pilot study using Geographic Information System (GIS). The research was carried out on a semi-natural pasture in Sweden, where the geographic positions of one cow were recorded during 25 consecutive days during summer. The cow, wearing a GPS collar, was integrated in a herd of 53 Hereford cattle. Each location point registered for the animal was considered as a sampling unit (N=3,097). The spatial distribution of ground declivity, water sources, cattle tracks, and classes of woody vegetation cover (forest, grassland with trees and open grassland) were recorded. The storage, processing and data analysis were carried out using the Idrisi and GS+ softwares. Three occupation zones were identified in function of the variation in the space used by the animal, which were occupied in a cyclical pattern; with the animal moving from one zone to another in cycles of five days. It was also clear that the cattle distribution in the area was neither random nor uniform, and it was affected by environmental characteristics that act as conditioners on its distribution. These preliminary results suggest that definition of zones of occupation and the environmental conditioners are promising tools to understand the land use by cattle
43
Zambrano-Ballesteros, Andrea, Sabina Florina Nanu, José Tomás Navarro-Carrión, and Alfredo Ramón-Morte. "Methodological Proposal for Automated Detection of the Wildland–Urban Interface: Application to the Metropolitan Regions of Madrid and Barcelona." ISPRS International Journal of Geo-Information 10, no. 6 (June 3, 2021): 381. http://dx.doi.org/10.3390/ijgi10060381.
Full textAbstract:
Official information on Land Use Land Cover is essential for mapping wildland–urban interface (WUI) zones. However, these resources do not always provide the geometrical or thematic accuracy required to delimit buildings that are easily exposed to risk of wildfire at the appropriate scale. This research shows that the integration of active remote sensing and official Land Use Land Cover (LULC) databases, such as the Spanish Land Use Land Cover information system (SIOSE), creates the synergy capable of achieving this. An automated method was developed to detect WUI zones by the massive geoprocessing of data from official and open repositories of the Spanish national plan for territory observation (PNOT) of the Spanish national geographic institute (IGN), and it was tested in the most important metropolitan zones in Spain: Barcelona and Madrid. The processing of trillions of LiDAR data and their integration with thousands of SIOSE polygons were managed in a Linux environment, with libraries for geographic processing and a PostgreSQL database server. All this allowed the buildings that are exposed to wildfire risk with a high level of accuracy to be obtained with a methodology that can be applied anywhere in the Spanish territory.
44
Sun, J., M. Mao, H. Xiang, G. Wang, and Y. Liang. "THE REAL-TIME MONITORING SERVICE PLATFORM FOR LAND SUPERVISION BASED ON CLOUD INTEGRATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1581–85. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1581-2018.
Full textAbstract:
Remote sensing monitoring has become the important means for land and resources departments to strengthen supervision. Aiming at the problems of low monitoring frequency and poor data currency in current remote sensing monitoring, this paper researched and developed the cloud-integrated real-time monitoring service platform for land supervision which enhanced the monitoring frequency by acquiring the domestic satellite image data overall and accelerated the remote sensing image data processing efficiency by exploiting the intelligent dynamic processing technology of multi-source images. Through the pilot application in Jinan Bureau of State Land Supervision, it has been proved that the real-time monitoring technical method for land supervision is feasible. In addition, the functions of real-time monitoring and early warning are carried out on illegal land use, permanent basic farmland protection and boundary breakthrough in urban development. The application has achieved remarkable results.
45
Caldas, Anildo, Teresa Pissarra, Renata Costa, Fernando Neto, Marcelo Zanata, Roberto Parahyba, Luis Sanches Fernandes, and Fernando Pacheco. "Flood Vulnerability, Environmental Land Use Conflicts, and Conservation of Soil and Water: A Study in the Batatais SP Municipality, Brazil." Water 10, no. 10 (September 29, 2018): 1357. http://dx.doi.org/10.3390/w10101357.
Full textAbstract:
In many regions across the planet, flood events are now more frequent and intense because of climate change and improper land use, resulting in risks to the population. However, the procedures to accurately determine the areas at risk in regions influenced by inadequate land uses are still inefficient. In rural watersheds, inadequate uses occur when actual uses deviate from land capability, and are termed environmental land use conflicts. To overcome the difficulty to evaluate flood vulnerability under these settings, in this study a method was developed to delineate flood vulnerability areas in a land use conflict landscape: the Batatais municipality, located in the State of São Paulo, Brazil. The method and its implementation resorted to remote sensed data, geographic information systems and geo-processing. Satellite images and their processing provided data for environmental factors such as altitude, land use, slope, and soil class in the study area. The importance of each factor for flood vulnerability was evaluated through the analytical hierarchy process (AHP). According to the results, vast areas of medium to high flood vulnerability are located in agricultural lands affected by environmental land use conflicts. In these areas, amplified flood intensities, soil erosion, crop productivity loss and stream water deterioration are expected. The coverage of Batatais SP municipality by these vulnerable areas is so extensive (60%) that preventive and recovery measures were proposed in the context of a land consolidation–water management plan aiming flood control and soil and water conservation.
46
Bouchachi, B., and Y. Zhong. "MONITORING URBAN LAND COVER/LAND USE CHANGE IN ALGIERS CITY USING LANDSAT IMAGES (1987–2016)." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 14, 2017): 1083–90. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-1083-2017.
Full textAbstract:
Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.
47
Schwartze, Christian, Franciska Zander, Sven Kralisch, and Wolfgang-Albert Flügel. "Virtual Appliances for geospatial data management and processing in the Integrated Land Management System (ILMS)." Acta Agraria Debreceniensis, no. 49 (November 13, 2012): 59–62. http://dx.doi.org/10.34101/actaagrar/49/2480.
Full textAbstract:
Virtualization is increasingly taking on a key role in various system architectures which follow new platform concepts like Software as a Service (SaaS). This trend addresses more instant and short-term environments and comes with new methods and strategies for the distribution of mainly complex application stacks not only in large IT infrastructures. The paper presents how a so called Virtual Appliance can be set up in order to operate in virtual server environments using hypervisor software like Oracle Virtual-Box. Using the example of two server-side components within the Integrated Land Management System (ILMS), it will be shown that the use of state-of-the-art methods, standardized tools and interfaces on servers enables different aspects of environmental system management, analysis and planning.
48
Nur, Achmad Surian, and M. Azhari Noor. "HYDROLOGICAL ASPECT OF BATANG ALAI WEIR WATERSHED DUE TO LAND USE CHANGES INTO MINING AREAS." CERUCUK 4, no. 1 (June 7, 2021): 61. http://dx.doi.org/10.20527/crc.v4i1.3579.
Full textAbstract:
The policy of the Ministry of Energy and Mineral Resources that provides permits for mining production activities for PT. MCM in the Batang Alai River area has an impact on the hydrology of the area. This study will discuss the changes in land use in the Batang Alai River area, Batang Alai Timur District, Hulu Sungai Tengah to the aspects of high flow and low flow hydrology. The research method used is manual calculation with rational methods for high flow hydrology and calculations using the ArcSWAT 2012.10.1.18 for low flow hydrology. The data needed in the processing are rainfall data, DEM data, daily discharge data, climatology data, land use data, land use change data, and Batang Alai watershed data. The results of the study were that the ratio of peak discharge of land use was changed to the mining area and land use was not converted into a mining area for high flow hydrology calculations. There is an increase in plan flood discharge in the Batang Alai River if there is a change in land use into a mining area, the design flood discharge always increases in each period. Whereas for low flow hydrology is the comparison between the daily use of land use converted into a mining area and land use is not converted into a mining area, then the daily discharge results are calculated for the availability of water. The results of low-flow hydrological modeling are categorized as good and have high influence based on the Nash-Sutcliffe efficiency value grouping and the coefficient of determination, and water availability decreases if land use is converted into a mining area.
49
Řezník, Tomáš, Jan Chytrý, and Kateřina Trojanová. "Machine Learning-Based Processing Proof-of-Concept Pipeline for Semi-Automatic Sentinel-2 Imagery Download, Cloudiness Filtering, Classifications, and Updates of Open Land Use/Land Cover Datasets." ISPRS International Journal of Geo-Information 10, no. 2 (February 23, 2021): 102. http://dx.doi.org/10.3390/ijgi10020102.
Full textAbstract:
Land use and land cover are continuously changing in today’s world. Both domains, therefore, have to rely on updates of external information sources from which the relevant land use/land cover (classification) is extracted. Satellite images are frequent candidates due to their temporal and spatial resolution. On the contrary, the extraction of relevant land use/land cover information is demanding in terms of knowledge base and time. The presented approach offers a proof-of-concept machine-learning pipeline that takes care of the entire complex process in the following manner. The relevant Sentinel-2 images are obtained through the pipeline. Later, cloud masking is performed, including the linear interpolation of merged-feature time frames. Subsequently, four-dimensional arrays are created with all potential training data to become a basis for estimators from the scikit-learn library; the LightGBM estimator is then used. Finally, the classified content is applied to the open land use and open land cover databases. The verification of the provided experiment was conducted against detailed cadastral data, to which Shannon’s entropy was applied since the number of cadaster information classes was naturally consistent. The experiment showed a good overall accuracy (OA) of 85.9%. It yielded a classified land use/land cover map of the study area consisting of 7188 km2 in the southern part of the South Moravian Region in the Czech Republic. The developed proof-of-concept machine-learning pipeline is replicable to any other area of interest so far as the requirements for input data are met.
50
Ali, Ircham, Vincensius Gunawan, and Kusworo Adi. "Land-use suitability evaluation for organic rice cultivation using Fuzzy-AHP ELECTRE method." Register: Jurnal Ilmiah Teknologi Sistem Informasi 7, no. 1 (January 19, 2021): 1–15. http://dx.doi.org/10.26594/register.v7i1.2080.
Full textAbstract:
Land conversion to organic agriculture is the answer to land degradation problems that interfere with land resources sustainability. An evaluation of land-use suitability is crucial to measure the appropriateness of land for agricultural cultivation. Specifically, organic rice cultivation has some particular standard criteria such as temperature, rainfall, soil depth, pH, c-organic, slope, erosion level, a transition period that influence ranking results, and land suitability classes. Eight organic farmlands were used as alternatives, namely Sawangan, Mangunsari, Tirtosari, Podosoko, Butuh, Krogowanan, Kapuhan, and Jati. Fuzzy Analytic Hierarchy process is used to determine the level of importance of the criteria based on weight assessments by three agricultural experts. The ELECTRE method is applied to rank the most suitable land from several alternatives for organic rice cultivation. The combination of these two multi-criteria decision-making methods complements each other to solve problems in land suitability evaluation. A web-based decision support system (DSS) was created to accelerate data processing integration and present factual information from the land suitability selection process. The implementation of DSS with fuzzy-AHP ELECTRE for evaluating land-use suitability in organic rice cultivation provided the best score for Tirtosari with Ekl=4 and spearman rank correlation the system comparison results with actual data rs=0.95. This study's results indicate that integrating the web with fuzzy-AHP ELECTRE is quite effectively applied for decision-making in organic farming.