Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: LULC classification methodology based on simple Convolutional Neural
  Network to map complex urban forms at finer scale: Evidence from Mumbai   The satellite imagery classification task is fundamental to spatial knowledge
discovery. Several image classification methods are used to create standardized
Land use and Land cover (LULC) maps, which facilitate research on spatial and
ecological processes and human activities. Local Climate Zones (LCZ)
classification maps are an example of standardized maps which have been widely
used to demarcate the homogeneity in built and natural character in the cities.
The LCZ classification scheme is primarily focused on urban climate-related
research, in which 17 climate zones are mapped in a city area with the 100-150m
spatial resolution. Each zone exhibits physical properties related to urban
form and functions essential for thermal behavior studies. Extending this
widely adopted approach to create LULC maps at finer resolution using the LCZ
mapping scheme would benefit the allied domains of urban planning,
transportation, and water resources management. This study proposes a novel
solution to generate classification maps with a 10-band Sentinel-2B dataset and
Convolutional Neural Networks (CNN) at the 10m spatial resolution. The
classification benefits from CNNs property to preserve local structures in the
image datasets. The proposed CNN model outperforms traditional machine learning
models such as Artificial Neural Network, Random Forests, and Support Vector
Machines. The overall accuracy and kappa statistic of the CNN model trained on
14 urban and natural classes are 82 percent and 0.81, respectively. The study
also discusses the utility of the model for specialized remote sensing tasks
such as change detection, identification of slum settlements, and mapping
pervious/impervious layers in urban settlements with higher accuracy.

24
The categories of this paper are: dg-ga
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an