Changes in glacier area, glacial lakes, debris cover, and geomorphological features such as debris fans have a significant impact on glacial dynamics. Therefore, precise and timely observation and tracking of glacier surface changes is a necessity. The availability of high spatial resolution remote sensing images has made it viable to analyse the glacier surface changes at a local level. However, with an increase in spatial resolution, the spectral variability increases, giving rise to additional challenges (such as false changes and misregistration) in the change detection process. These challenges can preferably be dealt with using an object-based change detection (OBCD) approach rather than the conventional pixel-based change detection approach. Therefore, this study has proposed an OBCD methodology using high-spatial-resolution remote sensing images to detect changes in glacier features. Variability in glacier features has been further analysed by associating it with important climate variables, that is, air temperature and precipitation. As a case study, the changes in Gangotri Glacier (Uttarakhand Himalayas in India) features have been studied using high-spatial-resolution WorldView-2 and Linear Imaging Self-Scanning System (LISS)-4 images for a 3-year period 2011–2014. The spectral correspondences between glacier surface and non-glacier surface have been handled by considering brightness temperature and slope as ancillary data to improvise their distinction. A change detection accuracy of ~ 84% has been obtained using the OBCD approach. Results further show that the variations in glacier features are in congruence with the climatic observations.

Glacier retreat represents a highly sensitive indicator of climate change and global warming. Therefore, timely mapping and monitoring of glacier dynamics is strategic for water budget forecasting and sustainable management of water resources. In this study, Landsat satellite images of 2000 and 2015 have been used to estimate area extent variations in 29 glaciers of the Bhagirathi basin, Garhwali Himalayas. ASTER DEM has been used for extraction of glacier terrain features, such as elevation, slope, area, etc. It is observed from the analysis that Bhagirathi sub-basin has a maximum glaciated area of ~ 35% and Pilang has the least with ~ 3.2%, whereas Kaldi sub-basin has no glacier. In this region, out of 29 glaciers, 25 glaciers have shown retreat, while only 4 glaciers have shown advancement resulting in a total glacier area loss of ~ 0.5%, while the retreat rate varies from ~ 0.06 m/yr to ~ 19.4 m/yr. Dokarni glacier has maximum retreat rate (~ 19.4 m/yr), whereas Dehigad has maximum advancing rate (~ 10.1 m/yr). Glaciers retreat and advance have also been analyzed based on terrain parameters and observed that northern and southern orientations have shown retreat, whereas the area change is highly correlated with glacier length. The study covers more than 65% of the total glaciated area and based on the existing literature represents one of the most exhaustive studies to cover the highest number of glaciers in all sub-basins of the Bhagirathi basin.

Rooftop rainwater harvesting systems (RRWHS) effectively provide water access by storing precipitated water. The amount of water harvestable using these systems is proportional to the availability of rooftop areas in the region. The use of satellite imagery has gained traction in recent times considering the challenges in conducting a manual survey to determine the rooftop area. However, the limitations on spatial resolution impaired stakeholders from conducting similar assessments in areas with small residential units. In this regard, the use of unmanned aerial vehicles (UAVs) providing high-resolution spatial imagery for the delineation of rooftops of all scales has become popular. The present study is an attempt to utilize UAV-generated orthomosaics to estimate the harvestable quantity of rainwater for setting up an RRWHS. A study area in the Gurgaon district, India, is selected, and the steps involved in estimating the quantity of water harvestable using UAVs are demonstrated. In addition to these computations, a suitable site for constructing the storage unit is identified with the aid of a weighted overlay technique implemented using a Geographic Information System. The results from the study show that nearly 11,229 m of water can be harvested per year in the study site using the RRWHS.

The Earth-Air-Heat-Exchanger (EAHE) is an effective solution for reducing energy demand. GIS based tools are commonly used to assess the suitability of EAHE sites, relying on geospatial data for geological and climatic parameters. However, lack of comparable data for different regions limits their applicability. In this regard, a framework that utilizes ERA5 reanalysis data to derive necessary geological and climatic parameters is proposed and demonstrated by considering India. Findings indicate that 25% of country's area falls under excellent category, benefiting 21% of the population. Additionally, 47% and 32% of the area are classified as moderate and good, respectively, providing thermal comfort to 51% and 28% of the population. Technical suitability of installing EAHE in an excellent category region is assessed through design and simulation study. Field studies are performed to collect climatic and geological parameters required for design. A computer model is developed using these design variables to determine the outlet temperature from EAHE. The simulation studies align with site suitability maps generated using GIS-MCDM framework, highlighting its reliability. Carbon footprint analysis reveals that EAHE adoption can reduce CO2 by 66.2% compared to conventional air conditioning units. The proposed GIS-MCDM framework can be extended to other regions lacking field data.