Mapping and monitoring the Trees outside Forests (ToF) is gaining
significance in the scientific community as they provide critical
ecosystem services such as protecting soil and water resources, wildlife
habitat, energy efficiency etc. Also, quantifying ToF can provide useful
information on emissions estimation in the Agriculture, Forests, and
Other Land Use (AFOLU) category of the Intergovernmental Panel for
Climate Change (IPCC). Despite the importance of quantifying ToF, very
few studies have attempted to quantify them in India’s natural resource
inventory programs. In this study, we focus on Haryana state, India, to
map ToF using very high-resolution (VHR) Indian Remote Sensing (IRS)
satellite data. Haryana’s landscape is highly interspersed with
croplands and ToF, thus providing a challenging environment to test VHR
satellite data’s ability to quantify the diversified landscape
structure. We specifically used Cartosat-1 panchromatic (2.5m) and
Multispectral LISS IV (5.8m) datasets to quantify the vegetation and
build a much-needed database on ToF. We used a novel classification
scheme based on the geometry, i.e., point, polygon, or polygon
formations, to quantify ToF at 1:10,000 scale. Our results suggest ToF
with the point, area, and linear block formations of about 2,774,531,
20.51, and 128.83 sq. km, respectively, accounting for
~3.38% of the total study area . Our study highlights
the usefulness of VHR satellite data and fused imagery to quantify ToF
in highly diverse landscapes, with the case study in Haryana State,
India. The results will help address vital ecosystem services from ToF,
including greenhouse gas emissions quantification from the AFOLU
category.
A comparison of forest resource inventory, provincial land cover maps and field surveys for wildlife habitat analysis in the Great Lakes – St. Lawrence forest
