Orchard Meadow Trees: Tree Detection Using Deep Learning in ArcGIS Pro

نویسندگان

چکیده

‘Orchard meadows’ refers to the combination of extensively managed fruit trees in with fields and pastures. In many regions, among others Germany, Austria Switzerland, they are a landscape-defining element particular ecological, economic social importance. However, numbers orchard meadows have been decreasing for quite some time. Current detailed data that allow identification suitable countermeasures maintain this cultural landscape often missing. Such can be obtained through deep learning. Various learning frameworks now used context ArcGIS Pro. But what exactly does use involve, Pro, get an insight into stocks meadow trees? What challenges? Initial analyses were carried out using selected areas Franconian Switzerland (Northern Bavaria) as example. The results confirm potential approach, but also training data, model output must refined.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Concept drift detection in business process logs using deep learning

Process mining provides a bridge between process modeling and analysis on the one hand and data mining on the other hand. Process mining aims at discovering, monitoring, and improving real processes by extracting knowledge from event logs. However, as most business processes change over time (e.g. the effects of new legislation, seasonal effects and etc.), traditional process mining techniques ...

متن کامل

ArcGIS Grows a Tree Model for the City of Trees

The ability of the GIS to assist governments in displaying and analyzing assets has grown from a utility based application to include many other features, including street and park trees. This paper will describe a case study in the design and implementation of an ArcGIS tree geodatabase model for use in Washington, DC, once known as the City of Trees. The model is used for general analysis as ...

متن کامل

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

متن کامل

Early detection of MS in fMRI images using deep learning techniques

Introduction & Objective:MS is a disease of the central nervous system in which the body makes a defensive attack on its tissues. The disease can affect the brain and spinal cord, causing a wide range of potential symptoms, including balance, movement and vision problems. MRI and fMRI images are a very important tool in the diagnosis and treatment of MS. The aim of this study was to provide...

متن کامل

Oil spill detection using in Sentinel-1 satellite images based on Deep learning concepts

Awareness of the marine area is very important for crisis management in the event of an accident. Oil spills are one of the main threats to the marine and coastal environments and seriously affect the marine ecosystem and cause political and environmental concerns because it seriously affects the fragile marine and coastal ecosystem. The rate of discharge of pollutants and its related effects o...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: GI Forum ...

سال: 2021

ISSN: ['2308-1708']

DOI: https://doi.org/10.1553/giscience2021_02_s82