<p><a>Indiana is the leading state of cover crop adoption within the Upper
Mississippi River Basin. However, since 2015 the cover crop adoption has slowed
to a plateau. In order to regain the previous momentum, there must be an
increased understanding of the spatiotemporal dynamics of cover crop adoption
on the county and watershed scale. Currently, the cover crop adoption is
monitored biannually through a driving transect survey method that investigates
only 8.5% of the watershed and extrapolates to the entire county. However, the
observations made by the driving transect survey can merely cover limited
fields and is time-consuming. In addition, the driving transect survey did not
provide comparative analysis among consecutive years. Therefore, we developed a
rapid cover crop survey method by using remote sensing technology. The
fundamental objectives of this research are: (1) evaluating the accuracy of the
rapid cover crop survey method relative to the driving transect data and
determining the best cut-off value (COV) of Normalized Difference Vegetation
Index (NDVI); (2) performing a hindcasting analysis of cover crop adoption
within the Big Pine Creek Watersheds within the period of 2014-2018 by
employing a rapid cover crop survey remote sensing techniques; (3) accessing
cover crop adoption management tendencies of farmers within the Big Pine
Watersheds, and (4) determining the cover crop adoption tenure of farmers
within the Big Pine Creek watersheds between 2014 and 2018. The cover crop
management tendency represents the farmers’ preference on cash crop rotation
method after harvesting cover crops, and the cover crop adoption tenure means
that how often farmers adopt cover crops in a specific field in the research
period.</a></p>
<p>The results of this research demonstrated that
relative to the conventional driving transect, remote sensing is a feasible
method to successfully detect cover crop adoption on a county and watershed
scale. Over a 4-year period (2015-2018), Producer’s Accuracy (PA) under the
best COV, which represented how much vegetation-covered field recorded in
transect data that can be captured in the processed NDVI map, was 89.02%. This
PA value was relatively high compared with previous spatial crop classification
research. The rapid remote sensing method also provided individual field
locations of cover crop adoption over time within the entire watershed,
compared to the driving transect that only gives extrapolated average of
adoption. The hindcasting analysis of cover crop adoption revealed a 74%
increase in cover crop acreage in the watershed from 2014 to 2018, which
equated to a 0.71% increase in land receiving cover crops among all cultivated
land annually. The evaluation of farmer cover crop adoption tendencies
demonstrated that over a 4-year period, cover crop adoption going into corn was
19.7% greater on average relative to before soybean. Another key finding was
that the level of cover crop adoption annually in the watershed was heavily
influenced by the cash crop rotation. The cover crop tenure analysis
demonstrated that agricultural fields of greater cover crop tenure represented
the smallest portion of the cultivated land in the watershed, where 84.2% of
the watershed was void of cover crop adoption and field that received cover
crops for more than 4 consecutive years represented only 1% of cultivated land.</p>
<p> To conclude, we are confident
that the rapid cover crop survey method could replace the traditional driving
transect survey. Our findings suggest that rapid assessment methods of cover
crop adoption involving processed NDVI map could help advance the
effectiveness, speed, and accuracy of cover crop adoption and assessment in the
state of Indiana and the entire Mississippi River Basin region.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/12741263 |
| Date | 31 July 2020 |
| Creators | Kanru Chen (9188216) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/EVALUATING_REMOTE_SENSING_TECHNIQUES_TO_RAPIDLY_ESTIMATE_WINTER_COVER_CROP_ADOPTION_IN_THE_BIG_PINE_WATERSHED_INDIANA/12741263 |
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