Development of Agriculture Land Evaluation Model Based on Environmental Risk
Date
2021-08-16Author
Sugiarto, Slamet Widodo
Hermadi, Irman
Setiawan, Yudi
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Show full item recordAbstract
Karawang district is one of the largest rice granaries in Indonesia. The
existence of agricultural areas is one of the important things that must be maintained
to support the national food security program. However, industrial development and
rapid population growth are factors in the conversion of agricultural land to non agricultural functions. The process of land conversion occurs massively on the
productive area with a small scale and is difficult to identify. Based on the
descriptions, it is necessary to evaluate agricultural land to support decision making,
especially in the conservation and management of agricultural areas in Karawang
district.
The objectives of this study are to introduce the alternative method for
improved image classification analysis based on hybrids time series normalized
difference index for rapid mapping of agriculture area and developing the spatially
explicit model to evaluate the potential of agricultural land to be converted based
on environmental risks.
The method introduced is a hybrid method by integrating the quantification
of the Normalized Difference Tillage Index (NDTI) and the characterization of the
Tillage Normalized Difference Vegetation Index (NDVI). The Normalized
Difference Tillage Index (NDTI) has been widely used to identify biophysical
parameters and agricultural practices. While the Normalized Difference Vegetation
Index (NDVI) is optimized for the characterization and analysis of agricultural
phenology. The hybrid method that integrates the quantification and
characterization of the Normalized Difference Tillage Index (NDTI) and the
Normalized Difference Vegetation Index (NDVI) promises a fast and precise
method for image classification. From the results of the accuracy assessment using
the Kappa coefficient, Producer accuracy is 95%, User accuracy is 71%, and
Overall accuracy is 72% with a coefficient of 31.4%. The use of Sentinel-2 data
with good spatial resolution can identify a unit area of less than 1 hectare, where
that the classification results can support precision agriculture activities.
The output of the Agricultural Land Evaluation model produces spatial
information that can explicitly describe the effect of each environmental risk
according to its weight. the agriculture area in Karawang district is dominated by
areas with high risk (39.66%), very high (32.95%), and moderate (24.21%).
Agricultural land objects with the highest and very high risk are adjacent to the road
network. Based on validation using serial very high-resolution data from 2017 to
2020 in West Karawang and Purwasari sub-districts, it was found that agricultural
areas with high and very high environmental risks have a high potential to be
converted into non-agricultural areas. The advantageous information would be
useful for decision-makers in determining priorities, management strategies, and
alternative scenarios for agricultural land conservation.