Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota
The growing demand for biofuel production increased agricultural activities in South Dakota, leading to the conversion of grassland to cropland. Although a few land change studies have been conducted in this area, they lacked spatial details and were based on the traditional bi-temporal change detec...
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doaj-4f541e4ecc88494eb3303bcf014dba482020-11-24T21:45:16ZengMDPI AGLand2073-445X2019-04-01845710.3390/land8040057land8040057Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South DakotaLan H. Nguyen0Deepak R. Joshi1Geoffrey M. Henebry2Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD 57007, USADepartment of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD 57007, USADepartment of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI 48824, USAThe growing demand for biofuel production increased agricultural activities in South Dakota, leading to the conversion of grassland to cropland. Although a few land change studies have been conducted in this area, they lacked spatial details and were based on the traditional bi-temporal change detection that may return incorrect rates of conversion. This study aimed to provide a more complete view of land conversion in South Dakota using a trajectory-based analysis that considers the entire satellite-based land cover/land use time series to improve change detection. We estimated cropland expansion of 5447 km<sup>2</sup> (equivalent to 14% of the existing cropland area) between 2007 and 2015, which matches much more closely the reports from the National Agriculture Statistics Service—NASS (5921 km<sup>2</sup>)—and the National Resources Inventory—NRI (5034 km<sup>2</sup>)—than an estimation from the bi-temporal approach (8018 km<sup>2</sup>). Cropland gains were mostly concentrated in 10 counties in northern and central South Dakota. Urbanizing Lincoln County, part of the Sioux Falls metropolitan area, is the only county with a net loss in cropland area over the study period. An evaluation of land suitability for crops using the Soil Survey Geographic Database (SSURGO) indicated a scarcity in high-quality arable land available for cropland expansion.https://www.mdpi.com/2073-445X/8/4/57land cover/land useagricultureCropland Data Layerland surface phenologySouth Dakotatrajectory-based change detectionmulti-date |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lan H. Nguyen Deepak R. Joshi Geoffrey M. Henebry |
spellingShingle |
Lan H. Nguyen Deepak R. Joshi Geoffrey M. Henebry Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota Land land cover/land use agriculture Cropland Data Layer land surface phenology South Dakota trajectory-based change detection multi-date |
author_facet |
Lan H. Nguyen Deepak R. Joshi Geoffrey M. Henebry |
author_sort |
Lan H. Nguyen |
title |
Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota |
title_short |
Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota |
title_full |
Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota |
title_fullStr |
Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota |
title_full_unstemmed |
Improved Change Detection with Trajectory-Based Approach: Application to Quantify Cropland Expansion in South Dakota |
title_sort |
improved change detection with trajectory-based approach: application to quantify cropland expansion in south dakota |
publisher |
MDPI AG |
series |
Land |
issn |
2073-445X |
publishDate |
2019-04-01 |
description |
The growing demand for biofuel production increased agricultural activities in South Dakota, leading to the conversion of grassland to cropland. Although a few land change studies have been conducted in this area, they lacked spatial details and were based on the traditional bi-temporal change detection that may return incorrect rates of conversion. This study aimed to provide a more complete view of land conversion in South Dakota using a trajectory-based analysis that considers the entire satellite-based land cover/land use time series to improve change detection. We estimated cropland expansion of 5447 km<sup>2</sup> (equivalent to 14% of the existing cropland area) between 2007 and 2015, which matches much more closely the reports from the National Agriculture Statistics Service—NASS (5921 km<sup>2</sup>)—and the National Resources Inventory—NRI (5034 km<sup>2</sup>)—than an estimation from the bi-temporal approach (8018 km<sup>2</sup>). Cropland gains were mostly concentrated in 10 counties in northern and central South Dakota. Urbanizing Lincoln County, part of the Sioux Falls metropolitan area, is the only county with a net loss in cropland area over the study period. An evaluation of land suitability for crops using the Soil Survey Geographic Database (SSURGO) indicated a scarcity in high-quality arable land available for cropland expansion. |
topic |
land cover/land use agriculture Cropland Data Layer land surface phenology South Dakota trajectory-based change detection multi-date |
url |
https://www.mdpi.com/2073-445X/8/4/57 |
work_keys_str_mv |
AT lanhnguyen improvedchangedetectionwithtrajectorybasedapproachapplicationtoquantifycroplandexpansioninsouthdakota AT deepakrjoshi improvedchangedetectionwithtrajectorybasedapproachapplicationtoquantifycroplandexpansioninsouthdakota AT geoffreymhenebry improvedchangedetectionwithtrajectorybasedapproachapplicationtoquantifycroplandexpansioninsouthdakota |
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