INTRODUCTION TO GEOGRAPHIC INFORMATION SYSTEMS CHANG PDF

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PDF | On Jan 1, , Kang-Tsung Chang and others published Introduction to Geographic Information Systems. Introduction to GIS - Kang Tsung suzuka-sc.info Ali Sajid. Loading Preview. Sorry, preview is currently unavailable. You can download the paper by clicking the. Trove: Find and get Australian resources. Books, images, historic newspapers, maps, archives and more.


Introduction To Geographic Information Systems Chang Pdf

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[Free] Introduction To Geographic Information Systems By Kang Tsung Chang Free Ebook [PDF]. [EPUB] Password requirements: 6 to Geographic Information Systems (GIS) to store, manage, analyze and This course is an introduction to the principles, techniques, and 2- Chang, K-T. ( ). download Introduction to Geographic Information Systems: Read 37 Books Reviews - suzuka-sc.info 8th Edition, Kindle Edition. by Kang-tsung Chang (Author).

However, implementation issues are little discussed, which means the reasons for the scarcity of large-scale implementations, which might be expected given the overwhelmingly positive results, are yet unclear. There is also little combination between GIS and mobile technologies. In order for health care processes to be effective they must integrate different kinds of existing technologies and data.

Further research and development is necessary to provide integration and better understand implementation issues. Keywords: health care, eHealth, mobile technology, mobile phone, SMS, text messaging, geographic information system, GIS Introduction The proliferation of mobile phones has provided a powerful communication channel to strengthen health information systems.

Functional and structural properties of mobile phones, such as low start-up cost, text messaging, and flexible payment plans, make them attractive to use for contacts with patients in various health care processes.

Often they are used to disseminate information to patients, but when used in conjunction with health care—related software apps, they can also provide real-time feedback needed to monitor treatment compliance or effect, and also serve as data collection tools. Further, back-end systems connected to mobile phones have the capability to serve as a platform for enabling preprogrammed, portable, automated services, which can make health care, and health information systems, increasingly decentralized.

Today, there is a lot of effort put into using mobile communication to improve various processes in health care, preventive as well as reactive. This is done in many ways, for example, by keeping doctors and patient better in touch eg, by reminder systems , by keeping local health care centers in better touch with central hospitals eg, by local doctors sending images for expert analysis , but also by providing preventive health information so as to decrease the number of people who become patients eg, by support in leading a more healthy life , and providing better statistics so as to better plan actions and resource allocation in the health care system, such as, in conjunction with natural disasters or epidemics.

Many, if not all, of the systems used for the above purposes require backend systems, or will at least perform better if they have such.

For instance, reminders to patients about visiting the doctor or taking their medicine must be integrated with a patient record so as to avoid a huge amount of manual labor. More generally, to be effective with respect to all stakeholders in health care, data collection systems should be technically integrated with systems for communication and decision making. As there is much health care data around, and many variables involved in making good decisions, medical as well as administrative, spatial, and economic, there is a need for effective data handling, analysis, and presentation.

For instance, health data from various regions in a country could be presented in geographic information systems GIS so as to provide better means of communication to decision makers.

It may make it easier to understand data by using graphical presentation, and it may make it easier to analyze data as they can be coupled with other data eg, regarding population, geography, and economy , which may distinguish different regions from each other. Taking all such factors into consideration may be necessary for the purpose of optimizing the allocation of available health care resources across a country and making sure effective methods are used everywhere.

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This research, therefore, looks into both technologies employed in operative processes of health care, the mobile phones, and technology aimed at providing support for decisions, the GIS, within health care. The study searches for cases where the two types of technologies are integrated and, based on the assumption that the integration would generally be as low as technology is relatively new, for clues to how best do this integration; what are the needs and the potential gains?

The purpose of this article is to provide a review of literature related to the use of mobile technologies and GIS in health-related research for improving health care.

The major topics for the review are the use of mobile technologies and GIS to improve health care. The research questions that served as the basis of this literature review are: What is the geographical distribution of publications on mobile technologies and GIS?

How have mobile technologies and GIS been used to improve health care?

What were the effects associated with the use of mobile technologies and GIS? Methods Search Criteria This is a literature study aiming at identifying the state of the art in mHealth, use of mobile phones for communication with patients, and GIS as well as research gaps. Still, the potential of the region remains large, but fuelling cocoa expansions will require well-structured efforts to i reduce barriers to transformation, ii ensure coupling of production to markets and iii adequate land use planning to avoid expansion of cocoa into natural forests 28 , 29 cocoa suitable areas do coincide with various protected areas within the Mesoamerican Biological Corridor.

Alternatively, by managing agroforestry systems, farmers could potentially maintain their current coffee and cocoa plantations using suitable trees to ameliorate microclimatic conditions.

This alternative could also prevent the expansion of agricultural activities towards protected areas that are reported to be suitable in the future However, it seems highly probable that current agroforestry schemes will need to be modified in terms of species composition, since some of the most popular tree species are also vulnerable to future climate.

It is particularly concerning the losses in habitat suitability of N-fixing trees such as E. These species make up the most abundant agroforestry trees in coffee and cocoa plantations in Mesoamerica 31 , 32 , and have a key role for the management of soil fertility and sustain more stable productivity 33 , 34 , especially in low-input and small farming plantations Therefore, our results anticipate a serious threat for future coffee and cocoa plantations if alternatives for N-fixing species are not promptly identified.

Rethinking current agroforestry species composition in coffee and cocoa landscapes requires the identification of the best tree species.

Geographic information system

Currently, farmers have a clear preference towards few species such as C. We found that some currently underutilised tree species in coffee and cocoa plantations could potentially maintain or even increase their suitable distribution ranges under future climate, such as the fruit trees M.

These species are present in low densities in coffee and cocoa plantations, and most of them are remnants of previous vegetation Expanding the use of underutilised species in agroforestry systems will require a deeper understanding of their agronomic performance considering other factors beyond just climate e.

In our assessment, we employed a species distribution modelling SDM approach disregarding these aspects.

Therefore, the interpretation of our results is driven by the expected changes in biophysical conditions characterised here as changes in extreme precipitation and temperature events. Here we show that coffee systems are more vulnerable than cocoa systems to climate change.

Not only is coffee more sensitive than cocoa to future climate, but also the tree species commonly used in coffee plantations are more vulnerable to the expected climate change. Cocoa as an alternative to coffee could potentially occur in most of the vulnerable coffee areas, but this will require addressing other ecological constraints, the impacts of pest and diseases, costs of technological change and market requirements to determine the real potential of cocoa to replace coffee. Adapting coffee and cocoa to changing climates can benefit from agroforestry systems with a new set of currently underutilised tree species already present in coffee and cocoa plantations.

The results of this study are a starting point to develop lines of research that support the re-design of agroforestry schemes and open new venues of research to adapt coffee and cocoa production systems in Mesoamerica.

From these species, 30 are mainly used due to their potential to improve soil conditions by fixing nitrogen, 37 species mainly used for timber products within the farm and potentially marketable and 33 species mainly used as fruit trees 44 , No distinction was made between locations from natural forests or farms because this information was not always available in the original sources.

Records with no geographic information or with obvious errors such as incomplete coordinates, locations in the ocean and mismatches between administrative data and coordinates were excluded from the analysis.

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For this, we compared the collected presence data and information on administrative boundaries with information from the DIVA-GIS database 49 , removing the mismatches. Presence locations from or before were also removed to meet the current baseline climate used. Finally we reduced the possible effects of sampling bias and spatial autocorrelation through systematic sampling This approach consists in create a grid of a defined cell size in our case 2.

In the Fourcade et al. Since absence locations were not available, for each species, we allocated 1, random pseudo-absence locations within the study area, which were sampled without replacement using the R 51 package dismo The bioclimatic variables include extreme or limiting factors that are ecologically important based on the variation in precipitation and temperature.

Which were: i bio02, mean diurnal range; ii bio03, isothermality; iii bio08, mean temperature of wettest quarter; iv bio09, mean temperature of driest quarter, v bio13, precipitation of wettest month; vi bio14, precipitation of driest month; vii bio15, precipitation seasonality; viii bio18, precipitation of warmest quarter; and, ix bio19, precipitation of coldest quarter. We focus on climate projections for to align with the United Nations framework of global challenges in agriculture Previous studies have shown that the consensus method based on weighted averages can significantly increase the accuracy of SDM For the model calibration, we performed a 4-fold cross-validation by randomly assigning without replacement location data to four bins.

The performance of different SDM algorithms was evaluated for each bin separately after algorithms were calibrated with data from the other three bins. Although some authors tend to criticise this method, the evidence 57 has shown that AUC has strong correlation with the presence-absence threshold that makes sensitivity equal to specificity and remains a valid measure of relative model performance.

Therefore, selected SDM algorithms were used to obtain the suitability model for coffee, cocoa and the tree species. We then applied the derived suitability model to each of the 17 downscaled GCMs to predict the distribution of suitability by the s.

Since there are no criteria to assess which of the GCMs best predict future climate, by incorporating all 17 GCMs we included all plausible changes in the distribution of the focal species. Organising the datasets relied on R packages magrittr 61 and tidyverse Layers were processed using the R packages maptools 63 , raster 64 , rgeos 65 and rgdal Data Availability Data and R code used is available through Dataverse References 1.

Introduction to Geographic Information Systems 8th Edition by Chang Test Bank

Altieri, M. The adaptation and mitigation potential of traditional agriculture in a changing climate. Change , 33—45 Google Scholar 2.

Ovalle-Rivera, O. Projected shifts in Coffea arabica suitability among major global producing regions due to climate change.A thorough search in prominent databases was conducted using predetermined keywords.

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