Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

نویسندگان

چکیده

Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes urban morphological distribution. Since the 1900s, urbanization has become underlying cause of LUCC, more than 55% world’s population resides cities. The speedy growth, development expansion centers, rapid inhabitant’s land insufficiency, necessity for manufacture, advancement technologies remain among several drivers LUCC around globe at present. In this study, or sprawl, together spatial dynamics Hyderabad, Pakistan over last four decades were investigated reviewed, based on remotely sensed Landsat images from 1979 2020. particular, radiometric atmospheric corrections applied these raw images, then Gaussian-based Radial Basis Function (RBF) kernel was used training, within 10-fold support vector machine (SVM) supervised classification framework. After maps retrieved, different metrics like Producer’s Accuracy (PA), User’s (UA) KAPPA coefficient (KC) adopted accuracy assessment ensure reliability proposed satellite-based retrieval mechanism. Landsat-derived results showed that there increase amount built-up area a decrease vegetation agricultural lands. Built-up only covered 30.69% total area, while it increased reached 65.04% after decades. contrast, continuous reduction land, vegetation, waterbody, barren observed. Overall, throughout four-decade period, portions have decreased by 13.74%, 46.41%, 49.64% 85.27%, respectively. These observed highlight symbolize characteristics “rural transition” socioeconomic modernized city, which open new windows detecting potential land-use laying down feasible future planning strategies.

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

Impact of urban land cover change on land surface temperature

The rapid growth in urban population is seen to create a need for the development of more urban infrastructures. In order to meet this need, natural surfaces such as vegetation are been replaced with non-vegetated surfaces such as asphalt and bricks which has the ability to absorb heat and release it later. This change in land cover is seen to increase the land surface temperature. Previous stu...

متن کامل

A CIESIN Thematic Guide to Land-Use and Land-Cover Change (LUCC)

Humans have been altering land cover since pre-history through the use of fire to flush out game and, since the advent of plant and animal domestication, through the clearance of patches of land for agriculture and livestock. In the past two centuries the impact of human activities on the land has grown enormously, altering entire landscapes, and ultimately impacting the earth’s nutrient and hy...

متن کامل

Multiclass Approaches for Support Vector Machine Based Land Cover Classification

SVMs were initially developed to perform binary classification; though, applications of binary classification are very limited. Most of the practical applications involve multiclass classification, especially in remote sensing land cover classification. A number of methods have been proposed to implement SVMs to produce multiclass classification. A number of methods to generate multiclass SVMs ...

متن کامل

Landsat 8 vs. Landsat 5: A comparison based on urban and peri-urban land cover mapping

An image dataset from the Landsat OLI spaceborne sensor is compared with the Landsat TM in order to evaluate the excellence of the new imagery in urban landcover classification. Widely known pixel-based and object-based image analysis methods have been implemented in this work like Maximum Likelihood, Support Vector Machine, k-Nearest Neighbor, Feature Analyst and Sub-pixel. Classification resu...

متن کامل

Multitemporal RADARSAT-2 Polarimetric SAR Data for Urban Land Cover Classification Using Support Vector Machine

This research investigates the various RADARSAT-2 polarimetric SAR features for urban land cover classification using object-based method combining with support vector machine (SVM) and ruled-based approach. Six-dates of RADARSAT-2 fine-beam polarimetric SAR data were acquired in the rural-urban fringe of Greater Toronto Area during June to September, 2008. The major landuse/land-cover classes ...

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: Remote Sensing

سال: 2021

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs13163337