Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automated Monitoring Cropland Using Remote Sensing Data: Challenges and
  Opportunities for Machine Learning   This paper provides an overview of how recent advances in machine learning
and the availability of data from earth observing satellites can dramatically
improve our ability to automatically map croplands over long period and over
large regions. It discusses three applications in the domain of crop monitoring
where ML approaches are beginning to show great promise. For each application,
it highlights machine learning challenges, proposed approaches, and recent
results. The paper concludes with discussion of major challenges that need to
be addressed before ML approaches will reach their full potential for this
problem of great societal relevance.

32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci