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Geographical Analysis - Science topic

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I am interested in seeing whether the focus of GIScience studies have shifted over the last few decades from being more local or regional in scale towards global. My assumption is that due to the availability and accessibility of global datasets (e.g. user generated data) and technical advancements that make it possible to analyse these datasets triggered a shift in geographic focus.
In a recent review of OpenStreetMap related publications, we found that 6.5% of analyzed publications had a global focus [1] . I was wondering if there are similar review papers that are broader in scope.
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You may find answers from this paper: “What Were GIScience Scholars Interested in During the Past Decades?”
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Hi everyone. I'm trying to specify the fruit tree types via ortophoto imageries at 25 cm resolution. In normal supervised classificstion techinques, I can seperate bare lands and trees. However, I need to specify fruit trees as a parcel which have same pattern. I have added a sample imagery. Please if it is posssible, suggest me any analysis, method or calculation in any GIS or RS software. Thank you for your intereset.
Sincerely.
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Fruit trees may be identified with more higher resolution rather than at 25 cm. However, in your case, First you classify the trees and mask them out from remaining part of image using supervised image classification. afterwards, you may reclassify the image using programming language like R and Python. It should be noted that at 25 cm resolution should be classified. If you can elaborate your outputs here, will be good to understand problem.
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Is there any research out there which someone tried to identify potential similarities of the tourist behaviour by a country in terms of sustainability?
For example, the Russians respect this but not this, the scandinavians mostly do this when in holiday and goes on...
I did a quick search in Google scholar but researchers doesnt seem to divide the tourists for simplier subjects than this. I understand that some countries are too big to have similarities but am asking if this idea have ever implement in some way.
Should this lead to a potential research about sustainability educations in each country?
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I follow this topic.
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As a part of my PhD, I conducted a study to assess health inequities in Amaravati capital region of Andhra Pradesh using two composite indices made from health determinants indicators and health outcome indicators.
Health outcome indicators data was available at the sub-district level. The data were interpolated to create a heatmap of the health outcome index. Whereas health determinants data was available at the village level. Thus I created a choropleth map using the health determinants index.
Later interpolated health outcome index map was overlayered on the choropleth map of health outcomes. It highlighted some interesting findings, i.e. areas of concern (Villages). The colour combinations created because of overlaying two layers revealed the areas with poor health outcomes and poor health determinants and areas with poor health outcomes with better determinants.
Kindly check these files and give your valuable opinions. Whether this type of analysis can be used to highlight the areas with health inequities or not? Please comment on the method used and the results obtained in the overlayered map.
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The OPGD model and "GD" R software package were recommended to identify spatial determinants from a perspective of spatial heterogeneity. You can refer the guide to use the model https://cran.r-project.org/web/packages/GD/vignettes/GD.html. As a result, you can visualise contributions of determinants, and the interactive impacts of spatial variables.
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I attempt to simulate how the greenhouse gases emission from soil surface under the set of determined crops (e.g. wheat, apples, citrus, sugarcane) depends on geographical position (it is the first step of simulation). The second step must be the analysis of changes because of climate change or irrigation.
Next, I'd like to compare GHG emission intensity with potential yield of crops for various countries of the World. The last is available on the web-site of Global Agro-Ecological Zones v3.0.
Can anyone advice, how I can get the data of GHG emission only from soil surface (but not because of fuel combustion by soil-tilling machines) for the major crops and for different country of the world.
I prefer the description of calcution method rather than ready for use online tools. Online tools often give uncertainties, which I can't trace under the following analysis of results.
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Very good question. Please have a look at these:
ELUM: A spatial modelling tool to predict soil greenhouse gas changes from land conversion to bioenergy in the UK.Environmental Modelling & Software ( 2016).
84 : 458-466.
Highlights :ELUM models soil greenhouse gas balance of bioenergy land-use change in UK to 2050. It is based on the ECOSSE model, but quick and easy to use, with added features. It is able to support life-cycle assessments and policy making for bioenergy. Consultation with anticipated users guided usability and functionality. Greenhouse gas balance is highly dependent on initial land use and new energy crop.
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When a population is small, the effect of genetic drift increases, leading to less allele fixation and/or random fixation. This, in essence, contributes to increased homozygosity, which affects species fitness negatively. Plant production can be affected by less efficient selection, which in small populations causes the accumulation of deleterious mutations. Since indivividuals are more likely to be linked to small groups, they are more likely to be inbred. Due to mutation accumulation, decreased genetic diversity, and increased inbreeding, a reduction in fitness may occur in small plant populations. The evolutionary ability and the capacity of a species to adapt to a changing environment, such as climate change, are diminished over time. Global warming, can lead to population fragmentation especially when coupled with mountains, reducing movement from one habitat to another
In forest areas, fragmantion can be claculated geographically and annual changes can be extracted. the situatin is differint in Scattered distribution of small herbs grow in mountain ecosystem, it is so difficult the calculate the fragmentation trend geographically (it’s not savanna or high covered forest that can calculate the yearly geographical changes), is there any method to calculate the fragmentation changes in population of such small herbs geographically?
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Mountain ecosystems are geographically very unique and the changes in plant populations of such ecosystems are need to be carefully monitored. In the scenario of climate change and global warming, genetic diversity is much essential to adapt the plant populations to the changing conditions.Remote sensing ( aerial photography)is one of the useful method to assess the fragmentation of plant population in mountain ecosystems.
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Aerial Laser Scanning Data is being more and more widely used across all Europe. Recently Great Britain decided to provide free access to aerial scanning data (starting on September 1st. 2016).
I know that Netherlands also provide free access to their laser scanning data (AHN 2 database of more than 600 billion x,y,z measured points)
I have also learned that Slovenia has released their LIDAR data as well, and also heard that North-Rhine Westfalia decided recently to open access to LIDAR data of their territory.
Are there any other EU States, which also decided to open free of charge access for their LIDAR datasets ?
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A nicely maintained list is here:
List of freely accessible LiDAR data and digital terrain models: https://arheologijaslovenija.blogspot.com/p/blog-page_81.html
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I would like to calculate the overlap between the distributions of two sets of data (predator & prey). The prey set has got about 250 species, the predator set approximately 5000. For each species I have a shape file in .shp format. Has anyone got any suggestions how to calculate the overlap between the pairs?
In the past I've used the function 'pairwiseRangemaps' of the fuzzySim package, but it calculates the overlap between EACH pair (so > 27 million comparisons for a 5250 x 5250 matrix), making it impossible to run on any normal computer (even splitting the data set in dozens of smaller files and taking out the upper triangle would take weeks or months). I'm not interested in the overlap between prey species or between predator species, just between each prey and each predator.
Has anyone got a suggestion how to calculate this in R? I'm thinking of two vectors (one prey, one predator) and then calculating the overlap between just these.
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Hi!! There are many ways to do that, if you do not have many polygons, you can do it with a simple clip and the calculation of the areas in attribute table. Then with the area of the complete and clipped polygon you can calculate the percentage of overlap. If you have many polygons, there are many functions to explore as those recommended the colleagues above. Depending on the software you use, you should google overlay polygons ArcGis, or QGIS, or R..
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I am interested in accounting for spatial dependency using spatial lag and spatial non stationarity using GWR in the same regression model. I am however wondering if there is an R package or software that can do this model (GWR-SL model).
If not, is it correct to do the spatial lag model and use the regression equation to estimate the value for each observation and include it as additional variable in the GWR analysis?
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To the best of my knowledge, GWR or MGWR accounts for spatial dependency as well as spatial heterogeneity. From Fotheringham et al. (2017) "... Hence, not only does GWR identify spatial heterogeneity in processes but it also takes advantage of the spatial dependence in data—so tying together the two main distinguishing features of spatial analysis."
Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale geographically weighted regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265.
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Hello everyone
I am currently a master student in Nevşehir Hacı Bektaş Veli University, Department of Geography, studying Physical Geography. My main areas of expertise are; İn additıon to geographical analysis, plant geography, data mining, map reduce and hadoop systems, land planning, plant taxonomy, I have been working on social media analytics and social media applications and analysis, social media and geography education in scientific and technical terms. But my main focus is on "Data Mining and Plant Geography modeling". I have a technical research article on this topic in my Research gate research account as full text. Study name "Creatıon of Plant Geography Databases Wıth The Map Reduce Modelıng ın The Clusterıng of the Large Geographıcal Data Sets". This study my Map Reduce and Hadoop systems and algorithms addition to data mining, GIS, plant geography research methods - techniques and various international plant databases, taking advantage of biological databases in Turkey and vegetatıon carried out ın the world, plant geography and so on. I tried to develop a new database model with this latest work that will contribute to the fields. In conclusion, I would especially like to listen and take advantage of the ideas and opinions of my colleagues and teachers working on data mining and geography, plant geography or vegetation, especially among geographers. Thanks to everyone who contributed in advance. Sincereley.
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Literature has been an object of study, a thematic context for research, a perspective through which the world is perceived, a methodological tool, and more. This relatively understudied field of geographic research, often titled “literary geography,” includes several overlapping perspectives following the main epistemological and theoretical turns in the fields of human and cultural geographies. In the early years, literature was often used to add aesthetic nuances to geographic descriptions or, slightly paradoxically, to function as a database for separating fact from fiction. Subsequently, before the 1960's and the rising interest in regionalism, literary geography was not actually geographic analysis of literature but rather a helping hand in descriptive geographic portrayals.
Quantitative revolution is among the enemies which ruined the field of literary geography and formed a separate field i.e quantitative geography.
Suggestions will be highly appreciated.
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We cannot all face one direction. If you need Mr A for medical advice, am sure Mr A will need you when he feels like traveling round the world or when at his leisure time.
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I have list of ~3000 geographical locations from various parts of India. I want to find out their Latitude and Longitude co-ordinates. I want to know if there is any tool / software that will together find out the co-ordinate and put the location on the map.
Thanks
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Google Maps has the most reliable and accurate database for geocoding (assigning lat lon coordinates to addresses), here are instructions for their API: https://developers.google.com/maps/documentation/geocoding/intro
If you're familiar with QGIS (https://www.qgis.org/en/site/forusers/download.html), you can install plugin called MMQGIS and easily geocode list of locations in CSV format, here are instructions how to download and use the plugin: https://www.lib.uwo.ca/madgic/projects/gis/Geocoding%20Using%20QGIS.pdf
You should prefer using Google as a source rather than OpenStreetMap (OSM).
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I have been trying to classify my images using fuzzy classification but the classification does not come out quite right especially if I increase the number of training area. any ideas on how to improve this?
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I need to calculate the area of landusetypes in 100m around various sampling point. For this i have two shp: Landuse file and sampling point file. I made a buffer with 100m diameter arround each point. My problem is, the buffers around the points are overlapping each over in some places. I tried to intersect/clip the layer (e.g. landuse) with the layer "buffer", but the many overlapping parts are combine in one area, only counted once. This overestimate area for some small part of intersection. My purpose is to have each intersection area individually. Is there any tool in qgis which might help me? Or is there any other way to get this output? Thanks for your help.
Please find attached how it looks like: Yellow is landuse data and circles are buffer arround sampling points(red dot)
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It is not in QGIS but in ArcGIS tool Count overlapping polygons can be useful.
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Geographic profiling is a tool used in criminology to identify an offender's residences by using the locations of the linked crimes. This is a tool used by police forces and investigative agencies around the world.
Recent studies in a series of papers made by Dr Steven Le Comber from Queen Mary’s School of Biological and Chemical Sciences, has shown that Geographic profiling can be used as an important tool in ecology. An example is to predict the the invasiveness of species and the spread of its disease.
How can this tool be utilized and be used in creating a major breakthrough in the field of ecology? What are its effects on the work of ecologists?
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we used it mainly with biological invasions. The important thing is that You have a database of georeferentiated data. If so we can also discuss it together
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I know is less than 10 degrees, however more accuracy would be ideal. 
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Thanks.  Theoretically you could download SRTM (Shuttle Radar Topography Data) and calculate the slopes from that (I would use GMT - Generic Mapping Tools grdgradient + grd2xyz, then sum z column for that,  but I presume arcGIS or similar offer similar functionality - the trickiest part will be to fillter out those values that belong to Europe, or to EU.  But I doubt this is the right approach - the average slope will be heavily skewed by mountaineous regions which will be just the regions without agricultural activities.  So you would somehow need to also include information on land use (e.g. using CORINE database on land use). You can see it gets complicated and really this would require a chunk of solid research.  I seriously doubt you will be able plug some number you found on the internet or a ResearchGate colleague might give you on this thread into some formula and expect to get a meaningful answer (I should point out that I am not a geographer, though)
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what are the softwares for doing spatial analysis?
To create maps
To compare maps
To do spatial analysis
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QGIS (http://www.qgis.org/zh_CN/site/) is the most commonly used free open source software for analysis and visualization of spatial data. It is user friendly, well-documented, equipped with hundreds of tools, and enables implementation of user's algorithms.
SAGA GIS (https://sourceforge.net/projects/saga-gis/) and GRASS GIS (https://grass.osgeo.org/) are also worth to consider. They can be installed as standalone, but they are additionally integrated in QGIS.
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First of all, thanks for this wonderful online tool!
I'm just wondering how are the geographic distribution established for each species?
I'm presently checking the validity of some fish species that are supposed to be present in La Réunion Island, SW Indian Ocean, i.e. species referenced in the French Taxonomical Reference Tool, TAXREF v10.0 (Gargominy et al., 2016) but not in the checklist established by Fricke et al. (2009).
I do not have problems when La Réunion of Mascarene Islands are cited in the "Distribution" field (or when fish species in TAXREF v10.0 are obvious errors, i.e. fish species restricted to the eastern Pacific Ocean!). But I do not know what to decide when the distribution field indicates for ex. "Red Sea, Indo-West Pacific: East Africa, Seychelles and Persian Gulf east to Philippines and New Guinea, north to southern Taiwan".
Thank in advance for your answer that will surely help users who encounter the same problem.
Regards
Dom
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Dear Ron:
Thanks for your rapid answer.  If you agree, I'll send you privately the list of species I found in TAXREF v10. For each, I'll add my estimate of the probability they really exist in La Reunion based on their geographic distribution in the Catalog of Fishes online.
Thanks again for the good work your are doing for all of us.
Best regards
Dom
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Hello,everyone!I have a question about GWR?How can I use GWR with raster data,for example how can I build the expression in raster calculator ? Looking for you reply!Thank you so much!
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Hi!
Here is a list of links with instructions on how to use GWR on raster data in different software environments:
QGIS-GRASS: 
ESRI ArcGIS: 
GWR function in R
GWR python library:
Hope this helps you get started with untangling your task :)
Good Luck!
Best regards,
Karolina
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I am trying to create a GIS using Graph database.
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Hy Ramana you can find a lot information of India here:
Best Regards
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I have a forest cover image having 5 land cover classes (very dense forest, mod. dense forest, open forest, scrub and non-forest) and a road shapefile with five types of roads. I'm thinking of creating a new image containing only two classes (forest and non-forest) and calculating fragmentation index (km/sq.km)(which is basically road density) per 10 km cell. But how do I calculate the index separately for each class? 
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We have addressed some of these questions in the past, and basically have to come up with some refined criteria for habitat, such as when is a low density forest with savanna understory a non-forest, and when does it function more like a forest such as a woodland with still some grassy or forb understory.  Also how small should the polygons go to be considered either forest or non-forest, how big should an inclusion be such as a small patch of trees in a savanna, is still functioning as a savanna, and a small opening in a forest is still forest.  I am unsure of a tull technical agreement, but such as a low density forest of 10-20 BA(basal area)/acre of trees with savanna understory is still considered grassland for habitat purposes.  Woodlands commonly 40 BA/acre of trees even with grassland understory from perhaps burning is often considered forest.  These kinds of decisions are typically best resolved by discussion or agreement with wildlife biologists, ecologists and foresters or silviculturalists, and may vary with the circumstances and importance of specific habitats and fragmentation to species involved.  Also you  might want to look at type of road, whether it is open for full time use, or a temporary or intermittent road, open seasonally or just for specific activities at some low frequency, but heavily grassed and relatively narrow in width, and closed to traffic uses and disturbances most of the time.  And it never hurts to analyze the problem with one set of criteria, and then reanalyze with one or more other sets to make a slightly different point relative to the situation.  In GIS, you can set and describe polygons of tree density or habitats and roads to perfect its utility to your subject, which probably has to do with habitat fragmentation.  The difficulty as your question suggests in how to best look at road fragmentation to a forest dominated landscape with mixture of non-forest.  The approaches you use will determine how best to accomplish.  If small inclusions of forest or non-forest of a select size are to be combined with the dominant land cover type, then that would be your first step, then decide if you want to evaluate any road or just certain types of roads, and whether skid trails or landings of timber that are still barren should or should not be included as a disturbance of habitat.
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Thank you for your time. Please discuss the optimizing parameters when you analyze the catchment area of the MRT station in (tropical) cities, include:
- distance
- direction and entrance of the stations.
- landscape design
- passenger behavior
-...
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Hi, I found some useful articles on principles and related strategies draw upon transit-oriented development (TOD) concepts. Hope they are of useful to your study.
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Hi everyone, I have a point data set with 197 different coordinates. I am selecting 25% to be used for training. When I run maxent with certain environmental layers, it is only using 8 presence records used for training, 2 for testing. Any ideas why this is?
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Thanks for the suggestions guys. I discovered it was a TWI layer I produced that was causing the problem. It was in a floating point pixel format which I have changed to signed 32 bit, the same as my other layers, and this seems to have done the trick.
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When I geocode large files in ArcGIS 10.3, I receive the following error, “There was an error trying to process this table.” In researching this issue, it says that one cause may be because the file is corrupt. However, this error goes away when I just cut down the number of cases I’m geocoding. Is there an easier fix for this issue?  
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I am looking for training and test date for classification of geographical points defined by longitude and latitude pairs. URLs to pertinent datasets most welcome.  The data  has to be classified though.
best wishes
Tony Scott
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Tony,
Not quite sure exactly what you are looking for. Are you wanting data like location, latitude, longitude? Like the link below
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I have polygons shape file and want to calculate the exact maximum length of all polygons together. To calculate the length of polygons individually is a lengthy process.  
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There is a Tool called Minimum Bounding Geometry. I don't know if it will offer you the ready data that you need but is very flexible and you can work things around. 
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I know that I need a projection that maintin the balance for the areas. However, I was wondering, if there is one particular projection that is more comonly used for this matter. 
Thanks!
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Dear Victor,
from what you wrote and please correct if I am wrong, you have to use an equal-area projection. That means that you have to use a measure-preserving dynamical system.
Examples of this kind of projections are: the Lambert cylindrical, Behrmann, Bonne, Mollweide etc.
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I am PhD student at University of Pretoria. Could you please assist me with tutorials for analyzing LULC changes for my study area using ArcGIS?  I do not have basic knowledge for GIS and Remote Sensing. Please email the tutorials to maggiemunthali2004@yahoo.com
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I am writing to overcome a problem that I am facing while using data. I am willing to use the optimal fingerprinting method and the problem pops up when I want to use the downscaled historical data of CORDEX as I want to use the historical simulations of CMIP5 including ALL, NAT and GHG forcing but as I have noticed the only forcing of historical that has been downscaled is ALL . Would you mind telling me if other forcings of historical (NAT, GHG) and control run data are to be used as they are (not downscaled), and if I can simultaneously use downscaled historical ALL (CORDEX) with historical (NAT, GHG) of CMIP5 which have not been downscaled? If the case is that these should all be downscaled to be used, would you please lead me to the right track of how to downscale them to be used with historical ALL (CORDEX).
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Hi Tofigh,  I am not an expert in this process, but doing spatial analysis all comes down to similar problems-missing data. Would using the average of both controls work?
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If I know a GPS position, how can I get the site GPP data?
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Thanks  so much Tiago. I only want to get one site's GPP (e.g., N 47.7790
E 107.7980), I can not find it from the website you provided. BTW, Can I get the data from 2014 until recent, like october, 2015?
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RAN, INEGI or other data representing distribution of private property parcels and federal property (not protected areas) in SE Mexico.
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hi
yes why not
Hossam
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Can anyone tell me who first used the landscape metrics or spatial metrics to analyze the urban spatial pattern or configuration?
If possible, please provide a relational reference.
Thank you!
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The first mathematical formulation of urban land use may be attributed to:
Johann Heinrich von Thünen for his (1842) formulation of land rents and the idealization of urban-agricultural regions in concentric circles. 
For a modern revisit of von Thünen's formulation:
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I am trying to delineate agriculture tile drainage in Midwest. I wonder if anyone has come across with GIS and sub-surface remote sensing techniques to detect tiles/objects buried in shallow depth of soil. Does anyone have any suggestions as to what type of remote sensing can be used to detect subsurface features? I can think of GPR (ground penetrating radar). Any other suggestions would be appreciated.
Thanks in advance !
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You might look at our use of UAV-based thermal imaging described in the following article: 
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The analysis needs to be done at 30 m resolution.
Thanks!
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Have you tried Landsat at 30m, you could extract water bodies using object based classification in SAGA GIS open source software, as an indicator of water body disctribution (or lack of water bodies). Sorry that is all I can think of.  
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Dear all
My question looks simple. What is the exact  meaning  of DEM resolution and relationship between it and the real pixel size of a map and topographic map scale?
For example when a DEM is derived from a contour layer with 10 m intervals so what is that resolution?
Totally, are there any relation? 
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The resolution of a DEM commonly refers to its horizontal (x-y) resolution, meaning a 25m-resolution DEM has a real pixel size of 25x25m, where one elevation value is assigned to each pixel. There is no direct relation to the contour intervals used to derive the DEM (that would refer to the DEM's vertical resolution, which is rarely provided).
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after getting NDVI values  from landsat data, how do I then get sugarcane yield data from the image.
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You can also try other indices too. Here is a good collection of them with explanations - www.indexdatabase.de
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I have downloaded some mod13A3(month NDVI 1k). Owing to the large data amount, I want to mosaic these images by using MRT.
I have learnt how to batch mosaic images with equal interval like mod 13A1 (16 days), but there is a limit, for there is one sentence like "set /a DAY= %DAY% + 16" in the batched code.
Does anyone know how to deal with this question?
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Hello Yifan
You can try with the script developed by Babak Naimi, available in http://r-gis.net/?q=ModisDownload
The ModisDownload function allows to mosaic all images from the same date. In addition, you can also reproject the images at the same time.
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I want shorelines data (lat&long) and i can't find it for all of world , for Mesh construction in sms (http://www.aquaveo.com/software/sms-surface-water-modeling-system-introduction) , i have it for persiangulf ,, for us i can download it from noaa website (http://www.ngs.noaa.gov/NSDE/) but for elsewhere i don't know !!
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Have you tried the Global Self-consistent, Hierarchical, High-resolution Geography Database?
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I need its exact meaning
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Dear Subir,
Oro- is an element, from the greek, that makes up names with meaning of 'mountain'.
Orotemperate is a thermotype from temperate climates.
Thermotypes clasification are: infra-, thermo-, meso-, supra-, oro-, cryo-,
Have a happy New Year.
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I have a map in .jpeg format. I want to get latitude and longitude of that. So, it is necessary to convert it into a shapefile.
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Hi. Converting raster map (jpeg) into vector layer is quite a problem (it takes time, unless it can be done automatically, but it is usualy not the case). But it seems it is not necessary in Your case. Just do the georeferencing of the raster map and You will be able to read the coordinates. If there are no points of known position (even cartographic grid will work if you know the projection) on the map (georeferencing is impossible in that case), find some already existing shapefile of the area (e.g. a coastline) and try to fit your raster map to the one you have found. Good luck.
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How can we to compare levels of congruence between shape files and/or grid files?
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You are looking for areas of endemism as these are areas with species with the highest co-occurrence. So there are a lot of methods, PAE, NDM, nested clade-area, etc. Among these I suggest the NDM it is the best to be a spatially explicit method. I had a paper accepted (and should be published shortly in PlosOne) in which I propose a new method for identification of areas of endemism that does not use grid cells (like the above methods).
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I am going to programming MCDM algorithms in ARC GIS.Does anyone research about it?
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Thank you so much,everybody for your comments.
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Overland and channel flow routing is controlled by weather (rainfall volume, intensity, and duration) and land surface (spatial scale, slope, landuse, and soil) conditions. Different combinations of these conditions would result in different flow velocity and require different time steps in nature and in the model. How can I determine the right time step at different geographic units using available climate and spatial information and integrate them into one system?
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Thank you for all your answers! Could I use flow velocity to limit the time steps for every grid?  If this is workable, I should to confirm the flow velocity for every grid. Is there a calculating equation for flow velocity for every grid both considering the  weather (rainfall volume, intensity, and duration) and land surface (spatial scale, slope, landuse, and soil) conditions?  
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In aprticular I am interested in allotmetric equations using vegetation cover, precipitation, etc.
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You can estimate biomass by using dimensional parameters, i.e., canopy cover, length and width of diameters as has been done by Gholami Baghi et al. (2013). You can download the full pdf , Journal of Rangeland Science, 2013, Vol. 3, No. 4 Gholami Baghi et al.
You can use remote sensing techniques to get information on aboveground biomass and make measurements on large scales. For details see Mundava et al (2014). 
Remote sensing techniques have been used by Porter et al. (2014). They have developed regression models for estimating biomass yields using data from satellite and ground based remote sensing platforms in pasturelands of Montana.
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According to my perception, toposheet can be used for knowing land profile via contour, delineating drainage lines, possibility of contour bunding, doing morphometric analysis of the area.
If we want to generate DEM (Digital Elevation Model)  toposheet is  required,
If above answers are wrong please correct me, please give your expertise comment about above question
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You are right. Toposheets are used to prepare DEM and its derivatives required for watershed development. One more use is to georeference the area.
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When rocks are handled for sampling, the magnetic property may get affected. Since rocks are more rigid, how can you sample it without affecting its magnetic property?
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It is not clear, what are "residual magnetic properties" which you want to maintain. For what purpose and how long do you intend to maintain this property?
Of course, there are magnetic properties which depend on size, volume, prehistory of sample etc. Some magnetic properties can be changed if we replace objects surrounding the sample or if we measure magnetic properties applying external magnetic field.
If elemental, phase and mineral composition of the sample almost the same as had the original rock, you can measure specific properties of sample material, like susceptibility, permeability, saturation magnetization, coercive force, residual magnetization, taking into account effects of size, shape... Statistics of results of sufficient number of samples also could help to understand properties of the original rock. 
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The calculation of stream power / unit stream power have to challenge the following problems :
- Estimation of bankfull decharge
- Estimation of channel slope
How to estimate or approximate them from old maps in order to propose stream power change ?
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Your question is indeed a bit too general to answer.
It is a topographical map I guess.... in such a case I would advise you to digitize it and from ArcGIS or any other open-source software like QGIS, you could define the channel slope and then the cross-section calculation necessary + knowing what is at the bottom of your chenal (or should be) for the roughness parameters....
The real question comes as Kazimierz said from the map scale... as I guess you will want to do comparison with present-day discharge.... and you will need to make sure that you pick the coarsest scale as a reference scale for the different measurements.
J'espere que c'est ce que tu voulais!
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The water quality model requires input of a bathymetry file of the form (.npt). This can be developed from a digital elevation model (DEM).
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Thank you, I later found that out and bought WMS.
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I have a raster and interested to calculate median in zonal statistics in QGIS . I tried grass but could not found values for each county   
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Thanks Pino Cosentino. It was quite easy with  saga . 
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Is it effective to use results of measuring length of a statistical self-similar fractals suggested by L.F. Richardson and B. Mandelbrot (L(G)=M*G1-D )for measuring geographical boundaries
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Thisal,
Your Question(s) are a bit ambiguous to me. Here is the justification:
1 - In the title you asked: What are the methods of measuring the LENGTH of a statistical self-similar fractal? So the unknown is the LENGTH of the fractal boundary.
2 - in the body of the question you asked: Is it effective to use results of measuring length of a statistical self-similar fractals...for measuring geographical boundaries?
So this is a completely different question.
For your convenience, I am going to answer both questions:
1 - To measure the length of a deterministic fractal boundary (or a curve in general), we need to set the smallest possible measure on our scale and add the corresponding measures of all the disjoint sets forming the fractal curve. I.e. we are applying a direct property of the measure theory which is: Measure (disjoint sets) = Sum of the measure of all sets.
2 - Since the geophysical boundaries are somehow "stochastic" in their structure, It is tough to apply the methods of the measurements of the deterministic fractal (particularly if you cannot determine the Hausdorff dimension). As a result, It is not a rigorous method to estimate the length of the physical boundaries using the technique of part (1).   
Hope my answers satisfy your inquiries!
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I want to make geographic transformation of WRF-ARW results to lat-lon projection like with UPP tool of WRF-NMM. I search for linux scripts or tools similar to UPP.
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Hello Malleswararao, 
I'm sorry I didn't answer your question earlier... It seems like you didn't have the netCDF libraries installed, or if they are in your computer, the CDO can't find them, since you're trying to work with a .nc file (the extension for netcdf files). 
You can find the netcdf package here: http://www.unidata.ucar.edu/software/netcdf/
Perhaps, you will need to recompile the CDO with netcdf support enabled. 
Good luck & regards!
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I am looking for a software can measure the length of curves (the red region). Can someone recommend some easy (preferably free) way to do this?The circles are in tangent to each other.
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You can transform the arcs in polylines and in the list of properties to get the corresponding lengths:
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Sometimes, I want to use a map from Google Maps or a similar website, but it may contain many names that I do not need or may not contain some names required. Also, the map size (especially in Google Maps) may be unsuitable. I need a software that helps me draw the map and edit it (add the pace names required along with the suitable size). Many online tools were tried but the result is not that level I desire.
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My district contains water towers (land with elevation above 1400m, a.s.l) and arable lands suitable for crop production (land of 1000 to 1400m a.s.l). Arable lands have easily erodible volcanic soils; therefore arable lands with steep slopes (30-60%) require terraces to be farmed and moderately steep slopes (15-30%) require contour farming. Given the district area DEM and landsat satellite image: (a) I want to create a map that shows Arumeru Rivers, water sheds and water sources.
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You can generate the surface model showing the elevation. Overlay with digital GIS layers of water bodies including, river, ponds and lakes. For the area demarcation regarding arable land you may choose to prepare the slope map and slope direction. An overlay map can be generated to find the suitable arable map, deducting the slopes not suitable for cultivation. Use overlay techniques and query tools to work on the raster maps. If you are using ArcGIS this would be feasible.
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If I tell you that I used 48 Landsat scenes in a study, what would you think I'm referring to: 48 different WRS2 Path-Row combinations, 48 images of the same Path-Row covering several years, or maybe 6 different Path-Rows with 8 acquisition dates each?
Although officially 'scene' refers to the individual data frame into which the satellite continuous data streaming is segmented, and thus it applies to the image data, I think we would be better served if 'scene' was reserved to refer to the area of the earth imaged in that path and row. That is, it would be good if there was a consensus that 'scene' is a synonym for 'tile' or 'map sheet' in the context of Landsat, so that folks know unambiguously what I'm referring to when I say that I used 48 Landsat scenes in a study.
What do you think?
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I just discussed this with a colleague, and we both agree that the use of the term "scene" is sometime misleading. However, the scene doesn't refer to an exact location. For sure, a scene has a size which is usually expressed in km at ground level, while an image size is expressed in pixel. Then why isn't a "scene" referring to a given "map sheet" ? Probably because there is no exact coordinate matching from a scene to another, even with Landsat. Landsat is very convenient since you usually get very close match within some classes of images. But there are still some differences from one image to another, especially if you perform an analysis over a long period of time : corner coordinate mismatch, row and column count mismatch, resolution mismatch (30m pixel was actually 28.5m), etc...
In the "NASA’s Global Orthorectified Landsat Data Set" (http://glcf.umd.edu/library/guide/PERSMarch_04_313-322.pdf), one can read "Data at these spatial resolutions can provide a high potential mapping accuracy of natural vegetation and alterations to it, if and only if highly accurate scene-to-scene within- and among-date registration is achieved."
Another thing : here, we more and more perform studies with mixed products, combining different sensors. Do you think it is relevant to re-define this term for Landsat-only studies ? Is it really still so informative to refer to a "scene" as being the sensor-specific covered area in this context ?
Anyway, very interesting question. This is not really an answer, just my two cents...
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I have implemented an algorithm which integrates two geographical datasets. Each record of both datasets must define its geographical coordinates (latitude and longitude) and a label (e.g. the name of the record). I would like to compare my algorithm with existing algorithms in literature.
Can anyone suggest any algorithm which integrates two geographical datasets? Thanks in advance!
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I've worked with geographical datasets for many years and have worked on similar problems. It helps a little to think of the problem as a nearest neighbor problem in 2D space. That brings together possible matches, but the crux of the problem is how to measure the similarity between two geographic features, that is, how to compute a distance function for each pair. For text similarity, there is the Levenshtein edit distance. I have usually improved on the basic algorithm. For comparing the geometry of 2 features, I have used dynamic programming algorithms. Levenshtein edit distance is itself computed by a dynamic programming algorithm, and the algorithm I have used for geometries is somewhat analogous. But those only deal with some of the complexity of integrating two geographic datasets. It is not simple.
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If we interpret the landslide points based on aerial images, when we want to get landslide susceptibility mapping, in case we extract non-landslide as training samples, how could we extract non-landslides points, because the landslide points not only one landslide?
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Well, a point is a very approximative representation of a landslide and will have an uncertainty, that is correct. If you have an idea about the mean size of the landslide bodies you could define the uncertainties of the landslides location represented by a point. Then it is appropriate to generate a buffer around the landslide points according to the uncertainty ( e.g. 20-50 m). After you can use the remaining area (ouside the buffers) for random sampling.Otherwise, even if you have no information of the landslide size you could still try the buffering, but then the buffer distance should be selected carefully. So you would most likely avoid to have landslide points in a non-landslide sample.
But a I have also a question, why are you using points to charcterize landslides from aerial images? What kind of images do you use (in which ground resolution)? What is the expected scale of analysis? Since you generate a sample for non-landslides points I guess you're giong to do a statistical analysis, logistic regression?
I'm asking because, if the resolution of the images allows the direct mapping of the landlide extent I would use polygons instead of points to do that. For high resolution images even a separation into source and deposition areas is recomended, since after you could gain additional information via magnitude-frequency statistics.
Best Regards,
Jewgenij
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Raster calculator seems not to be a solution?
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Do you have the metal concentration map?
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I'm searching for map sources that will provide me with reliable terrain type data for the given GIS location: Longitude 121.213 and Latitude 32.2343, terrain type is 'Forest' or 'Urban' or 'Water'.
I am currently looking at some ways to process sat/aerial imagery from Google Maps to create this type of data, but this approach is very unreliable since colouring/saturation/hue/contrast of images received from Google Maps is not constant. Very often, within same city, several different image qualities & colour settings will appear, some city areas will appear overall brownish, some greenish (as if white-balance was not set correctly when pictures were taken), and some will appear with natural colours. Creating data from these images often results in wrong terrain type detected.
So what I am looking for is map source that can give this type of information with acceptable reliability (I would consider 65% as acceptable reliability). Precision can be for wider areas, like 5x5 kilometers is just fine.
Can anyone help, give me advice or share some useful links?
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Hello,
Maybe this link will be useful for you:
Good luck!